Method for analysis of single pulse pressure waves

ABSTRACT

This invention relates to a method for analysing pressure-signals derivable from pressure measurements on or in a body of a human being or animal, comprising the steps of identifying during given time sequences in a series of time sequences the single pressure waves, including related parameters [pressure amplitude ΔP, latency (ΔT), rise time coefficient (ΔP/ΔT)], determining numbers of single pressure waves with pre-selected combinations of two or more of said single pressure wave parameters during said time sequence. For the time sequences is further determined the balanced positions of single wave parameters. Two-dimensional values of balanced position may be presented as a one dimensional value after weighting of the matrix cells. The signal processing method may be used for more optimal detection of single pressure waves by means of non-invasive sensor devices.

This application is a Divisional of coppending application Ser. No.10/613,122 filed on Jul. 7, 2003, and for which priority is claimedunder 35 U.S.C. § 120; and this application claims priority ofApplication No. 60/422,111 filed in United States on Oct. 30, 2002 andApplication No. PCT/NO03/00229 under 35 U.S.C. § 119; the entirecontents of all are hereby incorporated by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

Monitoring of pressures within human body cavities has an important rolein diagnosis and management of a large number of diseases and clinicalconditions. The present invention relates to a method for analyzingpressure signals derivable from pressure measurements on or in a body ofa human being or animal, comprising the steps of sampling said signalsat specific intervals, and converting the pressure signals intopressure-related digital data with a time reference.

Further, the present invention relates to a system for analyzingpressure-signals derivable from pressure measurements on or in a body ofa human being or animal.

More specifically, the invention relates to a method and a system asdefined in the preamble of attached independent claims 1 and 49.

2. Related Art

Continuous monitoring of pressures in humans and animals has awidespread place. During continuous pressure monitoring, today'sexisting technology, not the inventive technology (hereafter referred toas conventional or current technology) calculates a mean or area undercurve of several seconds of pressure recordings. For example, for agiven time sequence of 6 seconds, mean pressure may be computed as thesum of all pressure sample levels divided by the numbers of samples.Most modern monitors update the calculated pressure value each 5-10seconds. Thereby information within the single waves is lost. Whether ornot the mean pressure corresponds to single pressure waves during saidtime sequence is not known. Therefore, absolute numbers of systolic,mean and diastolic pressures shown on the scope of vital signs monitorsdo not reveal single wave distribution. The basis for this praxis is theassumption of a linear relationship between mean pressure and amplitudeof the single waves.

There are several problems with the current strategies of assessingcontinuous pressure recordings. Current technology uses calibration ofpressures against a zero pressure level, usually the atmosphericpressure. This situation raises various problems, such as drift of zeropressure level during a period of recording. Differences in absolutezero pressure levels may cause false or inaccurate differences inpressures between different pressure recordings, making it difficult tocompare pressure curves. Other causes of erroneous continuous pressurerecordings are sensor failure, misplacement of pressure sensor, lowquality of sensor signals related to movement of patient, and lowsignal-noise ratio of other reasons. Whether the quality of pressuresignals is good or bad may be difficult to decide according to currentstrategies of assessing continuous pressure signals. The presentinvention aims at solving these problems, introducing a new strategy ofanalysis of pressure related digital data, including assessment of thesingle pressure waves.

A continuous pressure signal fluctuates over time related to the cardiacbeats. In the human or animal body cavities, single pressure waves arebuilt up from the waves created by each of the cardiac pulsation's. Forexample, the intracranial and arterial blood pressure waves areintimately related as the intracranial pressure waves arise from thecontractions of the left cardiac ventricle. Each heart beat results in apulse pressure wave, termed single pressure wave. Related to the cardiacbeats, these waves have a diastolic minimum pressure and a subsequentsystolic maximum pressure. When it has not previously been possible totake the knowledge of single wave parameters into daily clinicalpractice, this situation is related to the facts that heart rate isvariable, single waves fluctuate a lot over time, and theinter-individual variation is large. So-called spectrum analysis orFourier analysis assesses fluctuations in pressure, but not by analyzingthe single pressure waves.

Non-invasive pressure monitoring is partially established for bloodpressure and ocular pressure monitoring, though no methods or devicesallows for continuous single wave monitoring with identification ofsingle wave distribution. In particular, applanation tonometry is anon-invasive method for intraocular pressure measurement, blood pressuremeasurement, and measurements of intracranial pressure in infants.

SUMMARY OF THE INVENTION

There are a number of human or animal body cavities in which pressuresmay be recorded for diagnostic and therapeutic reasons. For example,pressures in a human or animal body cavity relate to arterial bloodpressure, intracranial pressure, cerebrospinal fluid pressure, ocularpressure, urinary tract pressure, gastrointestinal tract pressure. Thepresent invention primarily was designed for analysis of pressuresignals derivable from monitoring of single waves in blood vessels, theintracranial compartment, the cerebrospinal fluid (CSF) system, theocular bulb and the urinary tract and bladder. These cavities represent,however, no limitation in the context of the invention. Other cavitiesmay be the esophageal tract, the anal canal, and others not specified.Thus, this invention is not limited to analysis of pressures from onlysome particular human or animal body cavities, as the invention relatesto a generic method for analysis of pressure derivable signals.

This invention relates to analysis of continuous pressure relatedsignals. Such pressure related data may be derived from a variety ofpressure sensors and pressure transducers. Independent of the type ofsensor, a continuous pressure signal is measured, providing theopportunity for sampling of single waves. Examples of such sensors aresolid or fiber-optic mechanical sensors for invasive monitoring, andsensors for invasive monitoring of pressure within a fluid system suchas arterial or venous blood vessels, cerebrospinal fluid, or urinarybladder/tract. There are various other types of sensors providingsignals indicative of pressures. Examples are sensors for non-invasivemeasurement of blood pressure, using principles of Doppler technology,or measurement of oxygen saturation, and non-invasive measurements ofintracranial pressure using Doppler technology or acoustic signals. Themost well-known principle of non-invasive pressure monitoring uses theprinciples of applanation tonometry. For example, applanation tonometryis used for monitoring of fontanel pressure in infants, and ocularpressure and arterial blood pressure. The unique with the presentinvention is the opportunity for determining single wave distribution bymore optimal detection of single pressure waves using the inventivemethod of analyzing single pressure waves.

More specifically, the method according to the invention is inventive,wherein for selectable time sequences the method further comprises thesteps of

a) identifying from said digital data single pressure waves, related tocardiac beat-induced pressure waves,

b) computing time sequence parameters of said single pressure wavesduring individual of said time sequences,

c) establishing an analysis output selected from one or more of saidtime sequence parameters of said single pressure waves during theindividual of said time sequences:

c1)—absolute mean pressure for each identified single pressure wave(wavelength Pmin−Pmin) within said time sequence,

c2)—mean of mean pressure for all identified single pressure waves(wavelength Pmin−Pmin) within said time sequence,

c3)—standard deviation of absolute mean pressure for all identifiedsingle pressure waves (wavelength Pmin−Pmin) within said time sequence,

c4)—numbers of single pressure waves during said time sequence,

c5)—single pressure wave derived heart rate during said time sequence,

c6)—relative pressure amplitude (ΔP) value for each identified singlepressure wave (wavelength Pmin−Pmin)within said time sequence,

c7)—standard deviation of relative pressure amplitude (ΔP) values forall identified single pressure waves (wavelength Pmin−Pmin) within saidtime sequence,

c8)—relative latency (ΔT) value for each identified single pressure wave(wavelength Pmin−Pmin) within said time sequence,

c9)—standard deviation of relative latency (ΔT) values for allidentified single pressure waves (wavelength Pmin−Pmin) within said timesequence,

c10)—rise time (ΔP/ΔT) coefficient for each identified single pressurewave (wavelength Pmin−Pmin) within said time sequence,

c11)—standard deviation of rise time (ΔP/ΔT) coefficients for allidentified single pressure waves (wavelength Pmin−Pmin) within said timesequence,

c12)—balanced position within a first matrix for combinations of singlepressure wave amplitude (ΔP) and latency (ΔT) values within said timesequence,

c13)—balanced position within a second matrix for combinations of singlepressure wave rise-time (ΔP/ΔT) coefficient values within said timesequence,

d) establishing a deliverable first control signal related to ananalysis output in step

c) for a selectable number of said time sequence windows, said firstcontrol signal being determined according to one or more selectablecriteria for said analysis output, and

e) modifying said deliverable first control signal into a regulatordeliverable second control signal said second control signalcorresponding to said first deliverable control signal, and

f) to provide a performance modifying signal.

Further embodiments of the method of the invention are defined insub-claims 2-48.

The system comprises, according to the invention:

-   -   a) control means which on basis of said pressure signals        receivable from a pressure sensor via pressure transducer means        is configured to control performance of a pressure sensor        regulating device to optimize single pressure wave detection,    -   b) a processing unit having means for analyzing said pressure        signals said processing unit including sampling means for        sampling said pressure signals at specific intervals,    -   c) converter means for converting the sampled pressure signals        into pressure related digital data with a time reference,    -   d) identifying means operative during selectable time sequences        to identify from said digital data single pressure waves related        to one of: cardiac beat-induced pressure waves, artifacts, and a        combination of cardiac beat-induced waves and artifacts,    -   e) analyzing means for analysis of said digital data single        pressure waves during said selectable time sequences,    -   f) output means configured to output to a regulator device one        or more first control signals derivable from one or more time        sequences parameters related to a selectable number of time        sequences elected from the group of:        -   f27) absolute mean pressure for each identified single            pressure wave (wavelength Pmin−Pmin) within said time            sequence,        -   f28) mean of mean pressure for all identified single            pressure waves (wavelength Pmin−Pmin) within said time            sequence,        -   f29) satandard deviation of absolute mean pressure for all            identified single pressure waves (wavelength Pmin−Pmin)            within said time sequence,        -   f30) numbers of single pressure waves during said time            sequence,        -   f31) single pressure wave derived heart rate during said            time dequence,        -   f32) relative pressure amplitude (ΔP) value for each            identified single pressure wave (wavelength Pmin−Pmin)            within said time sequence,        -   f33) standard deviation of relative pressure amplitude (ΔP)            values for al identified single pressure waves (wavelength            Pmin−Pmin) within said time sequence,        -   f34) relative latency (ΔT) value for each identified single            pressure wave (wavelength Pmin−Pmin) within said time            sequence,        -   f35) standard deviation of relative latency (ΔT) values for            all identified single pressure waves (wavelength Pmin−Pmin)            within said time sequence,        -   f36) rise time (ΔP/ΔT) coefficient for each identified            single pressure wave (wavelength Pmin−Pmin) within said time            sequence,        -   f37) standard deviation of rise time (ΔP/ΔT) coefficients            for all identified single pressure waves (wavelength            Pmin−Pmin) within said time sequence,        -   f38) balanced position within a first matrix for            combinations of single pressure wave amplitude (ΔP) and            latency (ΔT) values within said time sequences, and        -   f39) balanced position within a second matrix for            combination of single pressure wave rise-time (ΔP/ΔT)            coefficient values within said time sequence, and

g) regulator means connectable to said processing unit for receiving atleast one of said first control signals, said regulator means beingcapable of establishing a device performance modifying second controlsignal by means of at least one of said first control signals orestablishing a combination effect obtained from using at least two ofsaid first control signals, wherein said performance modifying secondcontrol signal deliverable from said regulator means being capable ofcontrolling said sensor regulating device.

Further embodiments of the system of the invention are defined insub-claims 50-74.

Thus, this invention is not limited to specific types of pressuresignals, however, the signal has to be continuous for a given timesequence. During continuous pressure monitoring, single pressure wavesare sampled along with a time reference. Analog pressure signals areconverted into digital pressure-related data. Since each wave representsa heart beat, the heart rate is known when the sampling rate is known.Determination of single wave distribution may be used in the real-timeand online monitoring of pressures. Processing of single waves may beperformed after sampling of pressure signals. Though data processing isperformed with some delay, monitoring is real-time since the delay hasno significance for the observed phenomenon. During identification ofthe single pressure waves, the continuous pressure signals undergofiltering and concatenation procedures wherein noise signals areremoved. Each single pressure wave is identified according to thediastolic minimum (P_(min)) and systolic maximum (P_(max)) values. FalseP_(min) and P_(max) values are removed. Identification of correctP_(min)/P_(max) values are made by means of pre-determined thresholdsfor the single wave amplitude (ΔP), latency (ΔT) and rise timecoefficient (ΔP/ΔT) values. For the correctly identified single pressurewaves, the single wave parameters [amplitude (ΔP), latency (ΔP), andrise time coefficient (ΔP/ΔT)] are determined for short time sequences(e.g. each 5 seconds). Such short time sequences with identified singlepressure waves are accepted or rejected according to selected criteria.The latencies represent the time sequence when pressures increases fromdiastolic minimum to systolic maximum, and the pressure change occurringduring this time sequence is the amplitude. The maximum (P_(max)) andminimum (P_(min)) values for the single waves are identified, and thematrix computed containing the amplitudes (ΔP) on the vertical columnand latencies (ΔT) on the horizontal row. Accordingly, the amplitudesare related to the naming of the columns and the latencies to the namingof the rows. The number or percentages of the single waves with thevarious combinations of amplitude and latency are computed within afirst matrix. The balanced position of occurrences of amplitude (ΔP) andlatency (ΔT) are determined. In a one-dimensional second matrix isplotted the number of occurrences of single pressure waves with a givenrise time coefficient (ΔP/ΔT) plotted, and the balanced positiondetermined. Furthermore, the absolute pressure values during said timesequence is determined, either as mean pressure for the whole timesequence or as mean pressure for the single pressure waves solely duringsaid time sequence. All of these single pressure wave parameters relatedto a recording sequence may be stored in a database.

Single waves are recorded repeatedly during a fixed time sequence (e.g.each 5 seconds). Such selected time sequences may have variousdurations, preferentially between 5 to 15 seconds. The actual heart rateshould not influence the results in this particular situation). Varioustypes of on-line presentation are possible. When balanced position ofamplitude (ΔP) and latency (ΔT) are plotted in a two-dimensionalweighted matrix, the balanced position may be represented as oneweighted value, e.g. in a trend plot (weighted value on the Y axis andtime on the X axis), or in a histogram (weighted value on the X axis andproportion or absolute number of occurrences on the Y axis). For thegiven time sequence, the numbers or percentages of single wavecombinations are presented within the histogram. On the Y-axis isindicated percentage occurrence of the various single wave combinationsof latency and amplitude, and the various latency/amplitude combinationsare indicated on the X-axis. For example, the bar within the histogramwith label on the X-axis of 0.2|3.5 indicates the percentage occurrenceof the single wave with a latency of 0.2 seconds and amplitude of 3.5mmHg in percentage of the total numbers of single waves during theactual recording time of 5 seconds. The matrix and/or histogram may besubject to a number of statistical analyses. In one embodiment it isuseful to determine the balanced position within the histogram ormatrix. This balanced position may be termed the centroid or the centreof distribution, though these terms represent no limitation of the scopeof the invention. In this invention the term balanced position ispreferred. Balanced position may refer to the balanced position ofoccurrences of amplitude (ΔP) and latency (ΔT) combinations in the firstmatrix (see Table I), or to balanced position of rise-time coefficients(ΔP/ΔT) in the second matrix. In this situation, balanced position isthe mean frequency distribution of the single pressure wave parametercombinations.

According to the invention the matrixes and histograms of single wavedistribution may be computed repeatedly online including alarm functionsfor the single wave distributions that may be considered as abnormal.Thereby, continuous update of single waves is an alternative way ofpresenting pressures. In such an implementation single wave distributionmay be updated each 5 or 10 seconds.

According to the invention, a method is described for more optimumanalysis of pressure signals from detection of single pressure waves bymeans of non-invasive pressure sensors. During short time sequences ofpressure recordings (e.g. each 3 seconds) the single pressure waveparameters are computed. Between each of said time sequences asensor-regulating device is modified by a regulator providing a controlsignal to the sensor-regulating device. Results of said analysis withinthe processing unit provide a control signal to the regulator that inturn provide another control signal to the sensor-regulating device.Thereby, the inventive method of single wave analysis may modify thefunction of the sensor device to give the most optimal single pressurewave detection. An example is described with regard to applanationtonomtery, though this represents no limitation of the scope of theinvention. A pneumatic pump and bellow press the transducer arrayagainst the skin and tissue above the cavity wherein pressure ismeasured (e.g. artery), usually referred to as the hold down pressure.In some devices the monitor searches through a range of pressure valuesuntil it measures an optimal signal in order to determine optimalhold-down pressure. Determining single wave distribution is however notpossible by these methods. The present invention enables optimum singlepressure wave detection. Furthermore, according to the presentinvention, there is no need for calibration by an independent technique.With regard to monitoring of fontanel pressure in infants basically thesame principles are used. In these cases, tonometry enables pressures tobe measured non-invasively on neonates. None of the techniques oftonometry provides the opportunity for sampling of single pressurewaves.

The particular features of the invention are described in the attachedindependent method claims, whereas the related dependent claims describeadvantageous, exemplifying embodiments and alternatives thereof,respectively.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows (a) parameters of a single pulse pressure wave, and (b) twotime sequences wherein single pressure waves are identified.

FIG. 2 shows (a) one time sequence wherein all maximum and minimumvalues in the continuous pressure signal are detected, and (b) theidentical time sequence wherein only the accepted minimum/maximum(P_(min)/P_(max)) pairs are shown.

FIG. 3 shows (a) one time sequence illustrating computation of absolutemean pressure for said time sequence according to two methods, and (b)relationships between absolute mean pressures computed according to thetwo methods for a large group of time sequences.

FIG. 4 shows (a) one time sequence wherein only false minimum/maximum(P_(min)/P_(max)) pairs are shown, and a trend plot of absolute meanpressure computed according to (b) the first or (c) the second method.

FIG. 5 shows two identical time sequences with identical time referencefor continuous (a) arterial blood pressure and (b) intracranial pressuremeasurements.

FIG. 6 shows a differential plot of two simultaneous continuous pressurerecordings with identical time reference with regard to (a) absolutemean pressure, (b) balanced position of amplitude, and (c) balancedposition of latency.

FIG. 7 shows the scatter plots for determining the best fitted curvesfor the relationships between (a) balanced positions of amplitude andlatency, (b) mean pressure and balanced position of latency, and between(c) mean pressure, balanced position of amplitude and balanced positionof latency.

FIG. 8 shows a sequence of events during real time monitoring of singlewave distribution, including (a) determination of single pressure waveswithin time sequences, (b) plotting combinations of single pressure waveamplitudes and latencies during said time sequence within a matrix, and(c) determining numerical value of balanced position of amplitude andlatency within matrix. The figure as well shows presentations ofweighted values of balanced position of amplitude and latency withintime sequences within (d) histogram, (e) trend plot, and (f)pressure-volume curve.

FIG. 9 shows the pressure curves and histogram presentations of singlewave distribution for intracranial pressure measurements within (a-b)the brain parenchyma and (c-d) the epidural space.

FIG. 10 shows two repeated pressure curves (a) before and (c) afterpressure reduction, including accompanying histograms of single wavedistribution (b) before and (d) after pressure reduction.

FIG. 11 shows trend plots of absolute mean intracranial pressure for twoindividuals (a, c), and trend plots (b, d) of weighted values (referredto as predicted mean pressure) of balanced position of amplitude andlatency combinations within said time sequences.

FIG. 12 shows (a) an overview of a system for interaction between aprocessing unit, a regulator and a sensor-regulating device, for moreoptimum (b) single pressure wave detection during said time sequences,also indicating (c) modifications in control signal level applied to asensor regulating device.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

With regard to sampling, analysis and presentation of single pulsepressure waves 1, relative differences in pressures are computed, notrelated to a zero pressure level such as the atmospheric pressure. Theinvention provides measurement and analysis of the following parametersincluded in the time sequences (FIG. 1):

a) Minimum (P_(min)) 2 is defined as the diastolic minimum pressure ofthe single wave, or as the valley of the wave. An individual singlepressure wave starts and ends with a diastolic minimum (P_(min)) value.

b) Maximum (P_(max)) 3 is defined as the systolic maximum pressure ofthe single wave, or defined as the peak of the wave.

c) Amplitude (ΔP) 4 is defined as the pressure difference when pressuresincrease from diastolic minimum pressure (P_(min)) to systolic maximumpressure (P_(max)).

d) Latency (ΔT) 5 is defined as the time interval of the single wavewhen the pressures change from diastolic minimum pressure (P_(min)) tosystolic maximum pressure (P_(max)).

e) Rise time coefficient (ΔP/ΔT) 6 is defined as the relationshipbetween amplitude divided by latency.

f) Wavelength 7 is defined as the duration of the single pulse pressurewave between the diastolic minimum pressure (P_(min)) 2 representing thestart of the wave and the diastolic minimum pressure (P_(min)) 2representing the end of the wave. Wavelength is referred to asP_(min)−P_(min) duration wherein first P_(min) is inclusive and endingP_(min) is not inclusive.

Whether the waveform is reproduced properly or not depends as well on asufficient resolution order and a sufficient sampling rate. In FIG. 1 ais shown a standardized single pulse pressure wave 1, indicating thevarious parameters of a single wave that may be analyzed quantitatively.A single intracranial pressure wave may contain three peaks, the first(P1) 8, second (P2) 9 and third (P3) 10 peaks. The maximum peak istermed the first peak (P1) 8 or top of the percussion wave. During thedeclining phase of the wave, there are two peaks namely the second peak(P2) 9, often termed the tidal wave, and the third peak (P3) 10, oftentermed the dicrotic wave. It is well known from the prior art that theabsolute pressure value may determine whether the various peaks arepresent or not. The maximum value (P_(max)) 3 usually is related to thefirst peak (P1) 8, but as pressure increases also the second peak (P2) 9may become the maximum value (P_(max)) 3. In this latter situation thesystolic maximum (P_(max)) 3 is represented by the second peak (P2) 9.It should be noted that the algorithm of defining single waves 1according to the maximum (P_(max)) 3 and minimum (P_(min)) 2 values, itis not always possible to determine whether the maximum (P_(max)) 3value represents the first (P1) or second (P2) peak. Not to introducemisunderstandings, the present invention relates to identification ofsingle pressure waves 1 according to the systolic maximum (P_(max)) 3and the diastolic minimum (P_(min)) 2 pressure values. Thus, in thepresent application, the amplitude (ΔP) 4 of the first peak is definedas the pressure difference between the diastolic minimum pressure(P_(min)) 2 and the systolic maximum pressure (P_(max)) 3, the latencyof the first peak (ΔT) 5 is defined as the time interval when pressuresincreases from diastolic minimum 2 to systolic maximum 3 pressures. Itshould be noted, however, that it is not always possible to exactlyidentify whether the top of the wave corresponds to the first peak ornot. Whether or not the various peaks are identified depends on samplingrate and/or resolution. Therefore, the method described here does notrequire that the different peaks (P1-3) are identified, in other wordsthe inventive method is not limited to the identification of thespecific peaks P1-P3. Thus, single waves 1 are identified according todiastolic minimum (P_(min)) 2 and systolic maximum (P_(max)) 3 values,independent whether systolic maximum (P_(max)) 3 is related to the first(P1) 8 or second (P2) 9 peaks. In practice it may be nearly impossibleto differentiate the first and second peaks.

In another embodiment reference may be to the second (P2) 9 and third(P3) 10 peaks. The maximum and minimum values may be specified for thedifferent peaks (P1-P3), wherein also the single pressure waveparameters amplitude 4, latency 5, and rise time 6 coefficients are withreference to each of the specific pressure peaks (P1-P3) 8-10. In thissituation, the identification of the first peak (P1) 8 is relative tomaximum 3 and minimum 2. The identification of the second peak (P2) 9also is relative to the first peak (P1) 8, and the third peak (P3) 10 isrelative to the second peak (P2) 9. This embodiment requires that eachpeak (P1-P3) is determined within the single pressure wave 1. Thereby,latency 4, amplitude 5, and rise time coefficient 6 may be withreference to each of said single pressure waves.

An important inventive step is the identification of single pressurewave parameters within given time sequences 11. A time sequence 11refers to a specified time period of pressure recording during acontinuous pressure monitoring. With reference to current technologyabsolute mean pressure of continuous pressure signals usually iscomputed within short time sequences 11 of 5-10 seconds. This is donebecause it is useful to update regularly the pressure values during atime of continuous pressure recording. In order to be comparable againstcurrent technology, the inventor select time sequences of between 5 and15 seconds duration. Thus, it is suggested that the lengths of the timesequences should be in the range of 5-15 seconds. The inventor found ituseful to use time sequences of 5 or 6 seconds. In the latter situation,a continuous recording period is considered as built up of a series ofnumerous continuous short time sequences of 6 seconds. The number of 6seconds time sequences 11 are 10 during one minute, 300 during 30minutes, 600 during 1 hours, 6 000 during 10 hours and 12 000 during 20hours of continuous pressure recording. The inventor considered these 6second time sequences 11 as the building blocks of the recording period.However, these suggestions of durations (e.g. 5 or 6 or 8 seconddurations) of time sequences 11 (or building blocks) should not beregarded as a limitation of the scope of the invention, as the timesequences might be of any duration selected by the user.

With reference to FIG. 1 b, on the x axis is indicated the time ofpressure recording 12, and on the y axis is indicated the pressurelevels 13. Along the time scale 12 two time sequences 11 each of 6seconds duration are indicated. The first time sequence 11 (named1^(st)) lasts from seconds 1-6 on the time scale 12, and includes eightsingle pressure waves 1 (numbered I-VIII). The second time sequence 11(named 2^(nd)) lasts from seconds 6-12 on the time scale 12, and alsoincludes eight waves 1 (numbered I-VIII). On the pressure scale 13 isindicated the absolute pressure levels, as well as giving an indicationof the values of the single wave amplitudes 4. As indicated in FIG. 1 b,the first single pressure wave 1 in the second time sequence 11 (named2^(nd)) is wave named I. This single wave 1 has its final minimum(P_(min)) 2 within the 2^(nd) time sequence. The inventor applied thecriterion that a time sequence 11 always starts with a single pressurewave 1 with complete wavelength 7 (P_(min)−P_(min)), wherein the finalP_(min) is within said time sequence. When considering the 1^(st) timesequence (named 1^(st)), the final wave does not terminate within the1^(st) time sequence but terminates within the 2^(nd) time sequence.Therefore, this wave is included in the 2^(nd) time sequence. In ordernot to exclude single waves from the analysis, criteria must be includedfor determining whether a single pressure wave 1 located between twotime sequences 11 should be located within the preceding or subsequenttime sequence. The strategy relies on selected criteria. This strategyrepresents no limitation concerning the concept of time sequences.

The method of analysis of continuous pressure signals described in thisinvention is applied to continuous pressure signals during such selectedtime sequences. The method is applied to all continuous pressure signalsfor each of said time sequences in a continuous series of said timesequences during a continuous measurement period. Accordingly, acontinuous pressure recording period is considered as built up of acontinuous series of said time sequences wherein said time sequences areaccepted or rejected for further analysis according to selectedcriteria.

Based on measurement of a continuous pressure signal, various strategiesmay be used to identify the single waves. Each pressure signal may beidentified on the time scale 12 because pressures are recorded alongwith a time reference. In one implementation, single waves areidentified according to the maximum (P_(max)) 3 and minimum (P_(min)) 2values. The following is an example of the procedure of identifyingmaximum (P_(max)) 3 and minimum (P_(min)) 2 values, though the exampleis not intended to limit the scope of the invention.

The procedure of sampling signals indicative of pressure and convertingsaid signals into digital data are described. The specific stepsdescribed here represent no limitation as several strategies may beused. The first part of the signal conditioning is the software filter.This filter removes a great deal of the high frequency noise. The sourceof the high frequency noise is not always possible to point out, but itwill always be present in many different shapes and magnitudes. Variousfilters may be used. The inventor found it useful to apply a 25^(th)order Bessel low pass filter, with a 25 Hz cut-off frequency. Otherfilters are available. The filter is programmed in a manner that removesboth the transient part and phase lag. This is done by taking a copy ofthe first 100 samples in the signal, and then reversing the order. Thenthe copy of the first 100 samples is concatenated to the originalsignal. This process is also repeated for the 100 last samples in thesignal. Then this signal is processed in the digital filter, thetransient part will appear in the “new concatenated” part in the signal.It will not destroy the original signal. In order to remove phase lag,the filtered signal is restored by taking a subset of data from thesignal processed by the filter algorithm. The subset is taken fromsample index 109, with a length equal to the original signal. Thespecific values referred to in this paragraph depend on samplingfrequency and other variables, and should not be regarded as limitationsof the scope of the invention.

Reference is now given to FIG. 2. Most of the pressure signals in thehuman body are very dynamic signals, which contain a lot of peaks andvalleys, not related to diastolic minimum and systolic maximumpressures. This paragraph describes the procedure of defining peaksrelated to systolic maximum pressure (P_(max)) 3 and valleys related todiastolic minimum pressure (P_(min)) 2. It should be noted thatdetermination of peaks (P_(max)) and valleys (P_(min)) may as well berelated to the specific peaks (P1-P3) within said single pressure waves1. The signals are also sometimes garbled with artificial signals. Inthis context peaks refer to maximum values and valleys to minimumvalues. The result may be a lot of unwanted maximum (P_(max)) 15 andminimum (P_(min)) 14 detections. An unwanted or artificial minimum(P_(min)) 14 value is a minimum value that does not represent thediastolic minimum of said single pressure wave, and an unwanted orartificial maximum (P_(max)) 15 value does not represent the systolicmaximum value of said wave. The peaks or valleys that are considered asunwanted or artificial depend on the criteria used during theidentification procedure. As indicated in FIG. 2 a, the procedure ofidentifying maximum (P_(max)) 3 and minimum (P_(min)) 2 values alwaysresults in a lot artificial maximum (P_(max)) 15 and minimum (P_(min))14 detection values. In FIG. 2 a all the detected minimum and maximumvalues are shown. In other words the peak and valley detections have tobe refined according to selected criteria. Therefore, wrong maximum 15and minimum 14 values have to be removed. A total of eight wrong maximum15 and eight wrong minimum 14 values are indicated in FIG. 2 a. Theacquired signal is first run through separate detection of minimum andmaximum values. The maximum peak threshold value (or peak) is set to thelowest level in the signal, with duration longer than predefined values.A variety of pre-defined values may be chosen. The minimum threshold (orvalley) is set to highest signal level, and the duration of the valleyis a pre-defined value, as described above. Subsequent to this analysis,all maximum and minimum values are represented with an amplitude valueand a location value or time stamp. This procedure will result in a lotartificial maximum (P_(max)) 15 and minimum (P_(min)) 14 detectionvalues. Therefore the maximum and minimum detection has to be refined.After refinement, the result is a collection of approved maximum(P_(max)) 3 and minimum (P_(min)) 2 pairs (FIG. 2 b) that may bepresented to the function handling the dynamic parameter analysis.First, grouping of the maximum values and minimum values is performed.For every maximum the subsequent minimum is found. This couple makes amaximum-minimum (P_(min)/P_(max)) pair. The latter maximum-minimum pairis inspected for threshold level. The threshold value has to be largerthan a given value. Subtracting the maximum amplitude and minimumamplitude performs this. The inventor found it useful to use thefollowing criteria for intracranial pressure: Amplitude (ΔP) 4 must bebetween 1.0 and 35.0 mmHg, and latency (ΔT) 5 between 0.10 and 0.40seconds. For arterial blood pressure, the thresholds were 30-120 mmHgfor amplitude (ΔP) 4 and 0.10 to 0.40 seconds for latency (ΔT) 5. Thesethresholds represent, however, no limitation of the scope of theinvention. Other thresholds may as well be used. The pre-defined valuesmay depend on age, and other variables such as type of pressure, type ofcavity wherein pressure is measured, as well as underlying diseases. Ifthe amplitudes (ΔP) 4 and latencies (ΔT) 5 are different from thepre-selected values, the pair is discarded. All the dynamic values arecalculated by using the approved minimum-maximum (P_(min)/P_(max))pairs. Only approved P_(min)/P_(max) pairs are entered into the timesequences for further analysis. Thus, an accepted P_(min)/P_(max) pairrefers to an accepted diastolic minimum (P_(min)) 2 value followed by asubsequent systolic maximum (P_(max)) 3 value, indicative of an acceptedsingle pressure wave 1. Criteria are applied as well to which diastolicminimum (P_(min)) 2 value that is considered to terminate the singlepressure wave. The values which are calculated are amplitude (ΔP) (deltaintracranial pressure expressed in mmHg) 4, latency (ΔT) 5, rise timecoefficients (ΔP/ΔT) 6, and heart rate 16. The latency (ΔT) 5 fromminimum to maximum is the time where the pressure of the single waveincreases from the diastolic minimum pressure (P_(min)) 2 to thesystolic maximum pressure (P_(max)) 3. Afterwards the P_(min)/P_(max)pair is inspected for the ΔP/ΔT 6 value. The ΔP/ΔT 6 value can beexpressed as (peak amplitude—valley amplitude) divided by (peaklocation—valley location). This will further remove P_(min)/P_(max)pairs caused by for example an artefact in the collected signal. AllΔP/ΔT values with a value equal or larger than a given value arediscarded. Another criterion is related to the wavelength duration.Since the wavelength is a measure of the heart rate, the heart raterepresents still another criterion. After applying the various criteriato single pressure wave detection, the collection of peaks and valleysnow contains only approved P_(min)/P_(max) pairs, corresponding toapproved single pressure waves.

With reference to FIG. 2 b, a total of 8 accepted P_(min)/P_(max) pairsare indicated. The individual single pressure waves 1 are indicatedalong with the time reference on the time scale 12, and the levels ofthe single wave amplitudes are indicated on the pressure scale 13. Theduration of said time sequence is 6 seconds. It is indicated that eachof these P_(min)/P_(max) pairs (i.e. single pressure waves) have adiastolic minimum 2 value followed by a subsequent maximum 3 value.Furthermore, the relation of the single pressure waves 1 to the timesequence 11 is indicated. The first 7 accepted P_(min)/P_(max) pairscorrespond to the first seven single pressure waves (waves named I, II,III, IV, V, VI, VII). The final accepted P_(min)/P_(max) pair has nonumber since this wave is not included in this time sequence 11. Thereason for this is that no accepted minimum 2 value was identifiedwithin the time sequence 11. Provided that such an accepted minimum 2value is determined within the subsequent time sequence, this wave willbecome the first wave in the following time sequence (see FIG. 1 b).

Thus, during a given recording period all single pulse pressure wavesare identified. However, due to artifacts some waves are missed. Thesoftware allows the computation of numbers of artifacts and missedsingle waves, as well as relates this to total counts of single waves.Hence, the artifact ratio may be computed. Given that the numbers ofartifacts are considered as too high a recording period may be omittedfrom analysis. Such artifacts relate to pressure recording sequenceswithout accepted single pressure waves (i.e. accepted P_(min)/P_(max)pairs). There are several reasons for not identifying single pressurewaves: Failure of pressure sensor may cause erroneous pressurerecordings. Noise in pressure signals is another reason. Theidentification of the correct single pressure waves provides theopportunity for only including those parts of the pressure recordingsthat include single pressure waves.

Measurement of single waves requires a continuous pressure signal,though the pressure signals may be sampled at a variable rate. Thesampling frequency preferably should be above 10 Hz. The inventorinitially found it sufficient to use a sampling rate of at least 100 Hzto identify maximum (P_(max)) 3 and minimum (P_(min)) 2 values. A highersampling rate (at least 200 Hz) may be required to find the maximumP_(max) 3 and minimum P_(min) 2 values for the individual peaks (P1-P3)8-10. When valleys (P_(min)) and peaks (P_(max)) are determined withreference to the specific peaks P1-3, said valleys and peaks arerelative to maximum values (P_(max)) related to systolic maximumpressure and minimum values (P_(max)) related to diastolic minimumpressure for said single pressure waves.

The invention is not limited to a particular range of samplingfrequencies. Rather the sampling rate should be sufficient to detect thevarious single pressure wave parameters (i.e. P_(min), P_(max), ΔP, ΔT,and ΔP/ΔT).

In summary, the procedure of identifying correct P_(min)/P_(max) pairsincludes different steps: (1) Filter and concatenation of digitalpressure signals. (2) All minimum (P_(min)) and maximum (P_(max)) valuesare identified and represented with an amplitude value and a locationvalue (or time stamp). (3) All P_(min)/P_(max) pairs are identified,where the subsequent minimum (P_(min)) value is found for every maximum(P_(max)) value. (4) Only those P_(min)/P_(max) pairs meeting certainpre-selected criteria concerning thresholds for ΔP, ΔT and ΔP/ΔT areaccepted. (5) The single pressure wave parameters for given timesequences are determined. (6) The time sequences are subsequentlyaccepted or rejected, according to criteria for the time sequences.

With reference to the time sequences 11, a question is which singlepressure waves that should be included. A time sequence may containparts of single waves both in the first and final part of the timesequences. It is not useful to discard waves of this reason. During acontinuous recording period, single pressure waves 1 occurring betweentwo time sequences are included in the first or second time sequenceaccording to selected criteria. The invention is not limited to whichcriteria that are used. The inventor used the following procedure:First, with regard to the final part of a time sequence 11, the inventorfound it useful to include in the time sequence 11 the single wave 1that is terminating within the time sequence 11, which is the singlewave terminating with its last P_(min) within said time sequence. Thus,the last single pressure wave 11 included within a time sequence 11 willhave its whole wavelength (P_(min)−P_(max)−P_(min)) within thatparticular time sequence, including its last P_(min). As indicated inFIG. 2 b, the accepted P_(min)/P_(max) pair subsequent to single waveno. VII is not included in the time sequence presented. If the lastaccepted P_(min)/P_(max) pair has no P_(min) the inventor found ituseful to use this wave in the following time sequence, provided afollowing time sequence is measured. Thereby, the single pressure wavesmay be immediately analysed for said time sequence without waiting forthe results of analysis of the next time sequence. Second, whenconsidering the first part of a time sequence 11, the first single wave1 will have its final P_(min) within this time sequence. With referenceto FIG. 1 b, in the second time sequence (named 2^(nd)) the first wave(named I) is the single wave with its final P_(min) within the secondtime sequence. The same aspect is indicated in FIGS. 5 a and 5 b.

In FIGS. 1 b, 2 a and 2 b are indicated on the pressure scale 13 (yaxis) the absolute pressure levels, which also give an indication of thevalues of amplitudes (ΔP) 4 of the single pressure waves 1. Theamplitude (ΔP) 4 values are relative values, not related to a zeropressure level, since the amplitude (ΔP) 4 levels represent the pressuredifference between the systolic maximum (P_(max)) 3 and diastolicminimum (P_(min)) 2 pressure levels. This is an important aspect of theinvention.

The absolute pressure levels of the single pressure waves 1 may as wellbe determined. The pressure scales 13 of FIGS. 1 b, 2 a and 2 b refer tothe absolute pressure levels that are relative to the atmospheric zeropressure level. The term absolute pressure refers to the situation whenpressure is relative to the atmospheric zero pressure level. Accordingto current technology, absolute pressures may be computed as mean oraverage of pressures during a time sequence of 5 seconds, and shown onthe Y-axis. The X-axis shows the time of pressure recording. Thefundamental difference between the curve according to the presentinvention and the conventional curve according to current technologyrelates to the strategy of processing pressure signals. According tocurrent technology, pressures may be processed in sequences of 5seconds, and the mean or area under curve for continuous pressuresignals during the 5 seconds period is computed. By this conventionalapproach information about single waves are missed. The time periodwherein mean pressure is computed may vary and depending on the monitorsystem. Furthermore, there is a wide range concerning pressure samplingfrequency. Most monitors compute mean pressure in sequences of 5-8seconds, though the term absolute mean pressure does not refer to aparticular recording period.

This invention introduces a new inventive step concerning computation ofabsolute mean pressure, related to time sequence. This method ishereafter referred to as Method 2, as opposed to Method 1, representingconventional or current technology. The differences between conventionaltechnology (Method 1) and the method according to this invention (Method2) are illustrated in FIG. 3 a. Given that absolute mean pressure iscomputed for a time sequence 11 of 6 seconds, current technology takesinto account all recorded pressure signals during the time period,indicated by the line termed Total in FIG. 3 a. Absolute mean pressurefor said time sequence 11 is the sum of all sample values (pressurelevels) divided by numbers of samples during said time sequence. Inequation 1 is shown the procedure of computing mean pressure (x=pressurelevel for each sample, and n=numbers of samples in the sequence).According to Method 1, a absolute mean pressure of 1.85 mmHg wascomputed for the time sequence presented in FIG. 3 a. $\begin{matrix}{{Mean} = {\frac{1}{n}{\sum\limits_{i = 0}^{n - 1}x_{i}}}} & (1)\end{matrix}$

The time sequence indicated in FIG. 3 a shows five accepted singlepressure waves 1 within said time sequence (named I, II, III, IV, andV). According to the criteria used, the pressure signals between singlewave III and IV were not indicative of single pressure waves. The basicconcept of this invention is that pressure values are only relevant whenrelated to single pressure levels, since pressure signals not indicativeof single pressure waves probably represent noise, not related topressure per se. Mean pressures computed according to conventionaltechnology does not take into account whether pressure signals arerelated to single pressure waves or not. This invention introduces a newinventive step, namely computing mean pressure for said time sequence 11as the sum of mean pressure for all individual single pressure waves(P_(min) to P_(min)) divided by the number of waves during said timesequence. Thereby, pressure samples not related to single pressure wavesare not included in determining absolute mean pressure for theparticular time sequence. For the time sequence presented in FIG. 3 athe wavelength (P_(min) to P_(min)) 7 for each individual single wave (Ito V) is indicated. In this situation the Formula 1 is applied to eachindividual single wave, wherein each wave begins and ends with adiastolic minimum value, equal to the wavelength (P_(min) to P_(min)) 7of said single pressure wave 1. According to equation 1, for eachindividual single wave, the sum of all pressure samples (pressurelevels) is divided by the numbers of samples. In this particularexample, the sampling rate was 100 Hz. Absolute mean pressure was 2.5mmHg for single pressure wave I, 2.27 mmHg for wave II, 2.96 mmHg forwave III, −0.45 mmHg for wave IV and 1.07 mmHg for wave V. Second, forthe whole time sequence, the sum of mean pressure for each individualsingle pressure wave during said time sequence is divided by the numberof single waves. Non-accepted single waves (or time sequences) are notincluded in the analysis. Mean pressure for the time sequence in FIG. 3a according to Method 2 was 1.67 mmHg [(2.5+2.27+2.96−0.45+1.07)/5].Actually the difference was small concerning absolute mean pressurecomputed according to Method 1 (1.85 mmHg) and Method 2 (1.67 mmHg).

In FIG. 3 b is shown the relationships between absolute mean pressurecomputed according to Method 1 or Method 2. On the y axis, the absolutemean pressure 17 refers to mean pressure computed according to Method 1,with reference to absolute mean pressure 18 computed according to Method2 on the x axis. Each plot in the scatter 19 refers to absolute meanvalues computed by either of the methods. Both methods were applied toindividual time sequences of 6 seconds during a series of continuoustime sequences in a total of 75 continuous pressure recordings. These 75continuous pressure recordings included a total of 873546 time sequences11, each lasting 6 seconds. Of these time sequences, a total of 144835time sequences were rejected according to selected criteria. No singlepressure waves were found in 20862 time sequences. Thereby, the plotpresented in FIG. 3 b is based on a total of 707849 time sequences, eachlasting 6 seconds. As indicated in FIG. 3 b, at the group level a veryhigh correlation exists between mean pressure computed according toMethod 1 and Method 2, as indicated by the regression line 20.

Despite a very high correlation between absolute mean pressures computedby either of the methods, a major advantage with the inventive method(Method 2) is that absolute mean pressure is computed only when singlepressure waves are identified. If no single pressure waves are acceptedor identified, no absolute mean pressure is computed. Method 1, on theother hand, computes mean pressure whether single pressure waves arepresent or not. Reference is now given to FIG. 4 that shows anintracranial pressure recording lasting about 11 hours and 54 minutes.This continuous recording period consisted of a continuous series of7145 time sequences 11. Only a total of 7 time sequences 11 wereaccepted, whereas 7134 time sequences 11 contained no single pressurewaves, and 4 time sequences 11 were rejected according to selectedcriteria. In FIG. 4 a is provided an example of one of the time sequence11 of 6 seconds that contained no single pressure waves. The absolutepressure levels were between 2 and 3 mmHg. As shown the pressure signalcontained only unwanted or artificial minimum 14 and maximum 15 values,not related to single pressure waves 1. According to Method 1, meanpressure for each time sequence 11 is computed as the sum of allpressure sample levels divided by the number of pressure samples. InFIG. 4 b, the mean pressure 17 according to Method 1 computed withineach time sequence each 6 seconds is plotted repeatedly against time inthe time scale 12. The mean pressure trend plot (pressure curve) 21consists of repeated plots, wherein each plot represents the meanpressure value of the 6 seconds time sequence 11. When only consideringthe pressure curve 21, it is not possible to know whether the curve isacceptable or not. Examples of absolute mean pressure trend curves 21are also shown in FIGS. 9 a, 9 c, 10 a, 10 c, 11 a, and 11 c. In FIG. 4c is shown another trend plot wherein the y axis shows absolute meanpressure computed according to Method 2 18 and the x axis the time scale12. No pressure curve was found in FIG. 4 c. Thus, computation of meanpressure within given time sequences according to the method describedhere (Method 2) gives the major advantage of not computing pressurevalues when single pressure waves are not identified. When singlepressure waves are present, the method gives absolute mean pressurevalues very similar to the absolute mean pressures computed according toconventional technology.

Reference now is given to FIGS. 5 a and 5 b. One single wave 1 has theduration from one minimum value (P_(min)) back to another minimum value(P_(min)), which is the duration of the wave (see FIGS. 1 a and 3 a).During a time sequence 11, the heart rate 16 may be computed accordingto two methods (HR-methods 1 and 2). According to the first method(HR-method 1), heart rate 16 is defined as equal to the number of singlepressure waves during said time sequence, divided with the duration ofsaid time sequence. With reference to FIG. 5 a, heart rate is equal to anumber of waves divided by recording time (seconds). During the firsttime sequence 11 of 6 seconds 7 single pressure waves were identified (Ito VII), giving a heart rate of 7/6 seconds (=1.2/second).

Another strategy (HR-method 2) is defining heart rate as numbers ofwaves divided by the total wavelength of said single pressure waves. Inone single pressure wave, the entire wavelength is defined as theduration from P_(min) to P_(min). The heart rate is the number of singlepressure waves during a time sequence divided by the duration of thetime sequence wherein these waves occurs. Heart rate method 2 issomewhat more accurate than Heart rate method 1, since the first methodonly includes the duration of the time sequence wherein single wavesoccurred. With reference to FIG. 5 a, the sum of wavelengths (i.e.P_(min)−P_(max)−P_(min)) of the 7 single pressure waves (I to VII) were5.7 seconds, heart rate would be 7/5.7 seconds (=1.2/second). Some minordifferences in heart rate may be computed by the two methods.

The invention includes through its methods of analysis at least twolevels of verifying whether a time sequence 11 includes correct singlepressure waves: (1) Criteria for accepting or rejecting single pressurewaves entering into the time sequences. (2) Criteria for accepting orrejecting the individual time sequence. If the time sequence 11 is notaccepted according to the criteria, the time sequence 11 is rejected forfurther analysis.

First, the main strategy for identification of single waves 1 arerelated to criteria applied to accepted P_(min)/P_(max) pairs concerningranges for amplitude (ΔP) 4, latency (ΔT) 5, and rise-time coefficients(ΔP/ΔT) 6. Single pressure waves not meeting the pre-selectedrequirements are rejected. A new time sequence 11 is started includingthe first accepted P_(min)/P_(max) pair, which is the first acceptedP_(min)/P_(max) pair that has its final P_(min) 2 within that particulartime sequence 11. This has been commented on for FIGS. 2 a and 2 b. InFIG. 2 a is indicated a total of 17 P_(min)/P_(max) pairs. After thesingle pressure wave criteria were applied to these 17 P_(min)/P_(max)pairs, only a total of 8 P_(min)/P_(max) pairs were accepted (FIG. 2 b).However, only 7 single pressure waves (I to VII) were included in thetime sequence, as the accepted P_(min)/P_(max) pair following wave VIIwas not followed by an accepted P_(min) value within the particular timesequence. Therefore, this latter accepted P_(min)/P_(max) pair wasincluded in the subsequent time sequence, provided that an acceptableP_(min) was identified.

Second, criteria may be applied to the individual time sequences 11,determining whether the entire time sequence is accepted or not. Thestrategy is related to the numbers of single pressure waves (or theheart rate) during the time sequence. During a time sequence the heartrate 16 should be within physiological limits. Ranges for numbers ofsingle waves within a time sequence may be defined. The inventor foundit useful to define that the heart rate should be 40-180 (i.e. 4 to 18single waves within a time sequence of 6 seconds). Thus, time sequencesof 6 seconds duration containing a number of single pressure wavesoutside 4-18 are not accepted for further analysis. Other criteria mayas well be used. In addition, thresholds may be defined for acceptedvariation of numbers of single waves within a time sequence. For severaltime sequences, standard deviation of numbers of single waves within thetime sequence may be computed, wherein time sequences with numbers ofsingle waves deviating too much from standard deviations are rejected.

When several pressures are monitored simultaneously with identical timereference, numbers of single pressure waves within identical timesequences may be compared, as illustrated in FIGS. 5 a and 5 b. Forexample, simultaneous monitoring of continuous arterial blood pressure(ABP) (FIG. 5 a) and intracranial pressure (ICP) (FIG. 5 b) with thesame time reference provides the opportunity to compare numbers of wavesfor these two pressures during identical time sequences. During a giventime sequence, numbers of single waves of ICP (N_(SW-ICP)) waves shouldbe nearly equal to numbers of single waves of ABP waves (N_(SW-ABP))[N_(SW-ABP)−N_(SW-ICP)<2). In the same way, heart rate (HR) derived fromsingle waves of ICP (or CSF_(p)) (HR_(ICP)) may be compared with heartrate (HR) of ABP (HR_(ABP)). During this recording period, thedifference of heart rate (HR) derived from these pressures should beless than 2 [HR_(ABP)−HR_(ICP)<2]. As illustrated in FIGS. 5 a and 5 b,the first time sequence (named 1^(st)) contains seven single pressurewaves (named I-VII), identical to the second time sequence (named2^(nd)). It should be noted that the numbers of single pressure waveswere equal (nos. I-VII) for both arterial blood pressure (FIG. 5 a) andintracranial pressure (FIG. 5 b). The specific numbers (<2) are only forillustrative purposes and should not be regarded as limitations of theinvention.

Comparisons between numbers of waves for one pressure type within a timesequence also may be compared against heart rate measurement fromanother source, for example pulse oxymetri (spO₂), orelectrocardiography (ECG). Heart rate 16 during a given recording periodderived from either arterial blood pressure or intracranial pressurewaves should be equal to heart rate derived from oxygen saturationmeasurements or by electrocardiography (ECG) [HR_(P-O2)−HR_(ICP)<2;HR_(ECG)−HR_(ICP)<2]. The inventor found it useful to use criteria fordifferences in single waves <2, though other criteria may as well beapplied.

For each time sequence 11, all the single waves and single waveparameters are known. Accordingly, standard deviations for all thesingle pressure wave parameters may be computed. Standard deviations forrelative pressures include the parameters amplitude (ΔP) 4, latency (ΔT)5, and rise time coefficient (ΔP/ΔT) 6 for all single pressure waves 1within the time sequences 11. Standard deviations for absolute pressuresinclude absolute pressure values such as mean pressure for allindividual single pressure waves (i.e. mean pressure from P_(min) toP_(min) for each individual of all single waves within the timeintervals), standard deviations for diastolic minimum (P_(min)) 2 forall individual single pressure waves during said time sequence, standarddeviations for systolic maximum pressure (P_(max)) 3 for all individualsingle waves 1 during the time sequence 11. Other criteria foracceptance or rejection of a time sequence may be related to limits forthe standard deviations referred to here.

Repeated up-dates are made concerning numbers/proportion of accepted andrejected time sequences (and single waves). A log is made for numbers ofrejected time sequences and numbers of rejected single pressure waves. Alog also is made for reasons of rejection, such as abnormal ΔP 4, ΔT 5,ΔP/ΔT 6, or abnormal changes in HR 16. Rejected portions of trend plotmay be indicated by color of graph or background. Examples of suchstatistics were made for FIGS. 3 b and 4 a.

After identification of the single pulse pressure waves 1 during arecording period, the single pressure waves are subject to analysis.Fundamental to the invention is the computation of a matrix 36 ofnumbers or percentages of single pulse pressure waves with pre-selectedwave characteristics. Examples of such characteristics are latencies(ΔT) 5 and amplitudes (ΔP) 4. The matrix 36 of amplitude (ΔP) 4 andlatency (ΔT) 5 combinations are referred to as the first matrix in thisdocument. Again, the latencies and amplitudes in the matrix presented inTables I, V and VI refer to single waves identified by diastolic minimum(P_(min)) 2 and systolic maximum (P_(max)) 3 values. As indicated, thegroup of amplitudes are shown on the horizontal row, and the grouping ofthe latencies on the vertical column. Each number 37 within the cells ofsaid matrix 36 represents the total numbers of single waves with thegiven combination of amplitude 4 and latency 5. In another situation thenumbers 37 may refer to percentages. When percentages are used, it isagainst total numbers of waves. The amplitudes 4 are usually expressedin mmHg and the latencies 5 in seconds. The numbers of cells in such amatrix 36 may differ depending on the number of columns and rows. Anexample is given based on experience of the inventor. For intracranialpressure, the inventor found it useful to use the range of amplitudes(ΔP) 4 equal to 0 to 30.0 mmHg, with intervals of 0.5 mmHg, giving atotal of 60 columns. The range of latencies (ΔT) 5 is 0.10 seconds to0.40 seconds with intervals 0.01 seconds, giving a total of 30 rows. Inthis matrix the total cell number is 1800. The example represents nolimitation of the scope of the invention. For arterial blood pressure,on the other hand, the inventor used the range of amplitudes (ΔP) from30 to 120 mmHg, with intervals of 2.0 mmHg, giving a total of 45columns. The range of latencies (ΔT) is 0.10 seconds to 0.40 secondswith intervals 0.01 seconds, giving a total of 30 rows. In this matrixthe total cell number is 1350. However, these are only examples, and arenot intended to limit the scope of the invention.

An example of a small part of a matrix applied to intracranial pressureis shown in Table I. The matrix 36 (referred to as first matrix)illustrate only a small fraction of a large matrix of 1800 cells. TABLEI Part of a matrix of amplitude (ΔP) and latency (ΔT) combinations.Group name 0.5 1 1.5 2 2.5 Group range 0.5 ≦ dP < 1.0 1.0 ≦ dP < 1.5 1.5≦ dP < 2.0 2.0 ≦ dP < 2.5 2.5 ≦ dP < 3.0 Group midpoint 0.75 1.25 1.752.25 2.75 0.1 0.10 ≦ dT < 0.11 0.105 0.11 0.11 ≦ dT < 0.12 0.115 0.120.12 ≦ dT < 0.13 0.125 3 12 0.13 0.13 ≦ dT < 0.14 0.135 16 12 8 0.140.14 ≦ dT < 0.15 0.145 7 5 4 0.15 0.15 ≦ dT < 0.16 0.155

The amplitude (ΔP) 4 values are presented in the columns and the latency(ΔT) 5 values in the rows. For example the first column corresponds tothe first amplitude (ΔP) group, named 0.5 (corresponding to 0.5 mmHg);this group includes amplitude (ΔP) 4 values greater or equal to 0.5mmHg, but less than 1.0 mmHg (indicated by the group range 0.5≦ΔP<1).The midpoint (or mean) of the group is 0.75 [(0.5+1.0)/2]. Similarly,the first latency group is termed 0.1, corresponding to a latency of 0.1seconds. This latency group includes latencies with a duration greateror equal to 0.10 seconds, but less than 0.11 seconds (indicated by thegroup range 0.10≦ΔT<0.11). The group midpoint is 0.105 [(0.10+0.11)/2].The amplitude/latency (ΔP/ΔT) matrix can be seen as a two dimensionalcollection of bins, where the rows are labelled ΔT and the columns arelabelled ΔP. A cell equals a bin. Each bin denotes how often ΔP/ΔTcombinations have appeared. When the observation is categorized orgrouped, the midpoint of the group is used. The data are categorizedwhen the data are in a “range”. As an example the first bin in thematrix presented in Table I contains all ΔP values which fall in therange greater or equal to 0.5 mmHg and less than 1 mmHg, with a ΔT valuegreater or equal to 0.10 seconds and less than 0.11 seconds. The matrixcells found at intersections between columns and rows indicate numbersor proportions of single pressure waves with specific combinations ofamplitude (ΔP) and latency (ΔT). The numbers presented in Table I refersto an intracranial pressure recording lasting one minute including 10time sequences 11, each lasting 6 seconds. During these 6 time sequencesa total of 67 single pressure waves occurred. The distribution of thevarious single pressure waves during this recording period is shown inTable I. For example, single pressure waves 1 with an amplitude (ΔP) 4greater or equal to 1.5 mmHg but less than 2.0 mmHg and a latency (ΔT)greater or equal to 0.14 seconds, but less than 0.15 seconds occurred 5times during the time sequence represented in this matrix.

During real time monitoring, the matrix may be computed each 5 seconds.The centre of mass of distribution (balanced position) of single waveswith combinations of latency and amplitude may be computed, withouttaking into account the heart rate. Another implementation may becontinuous update of single wave distribution each 5 or 10 seconds. Onthe monitor display a histogram is presented each 5 seconds in manymonitors, though there may be differences between the monitors. Theinvention does not give any limitations concerning the frequency ofupdates of matrix.

The preferable approach suggested by the inventor, is repeatedcomputation of the matrix during a continuous pressure monitoring. Foreach of said time sequences 11 the matrix 36 is computed. For example,with reference to FIG. 5 a, one matrix is computed for the first timesequence (named 1^(st)) and a new matrix computed for the second timesequence (named 2^(nd)). For the first time sequence 11 (termed 1^(st)),the matrix 36 contains the amplitude (ΔP) 4 and latency (ΔT) 5 values ofseven single pressure waves. For the second time sequence 11 (termed2^(nd)), a new matrix 36 is computed also containing seven singlepressure waves. For each individual time sequence, new ΔP/ΔTcombinations are subsequently entered into the matrix cells during theongoing pressure measurement. The matrix is updated dynamically duringsuch a 6 seconds time sequence, each cell is updated by adding the newvalue to the old content. After the 6 seconds interval the procedure isreiterated starting with a new and empty matrix.

The matrix 36 presentations may be subject to various types of analyses.The balanced position within the matrix may be presented as numericalvalue combinations 38 such as centroid or centre of distribution.According to the present invention, the single waves 1 with pre-selectedcharacteristics of latency 5 and amplitude 4 are computed, and thematrix 36 of single wave combinations computed, with presentation of thedistribution of single wave combinations. For the 5 second period thebalanced position of single wave combinations may be computed, forexample as centroid or centre of distribution. For example, acombination 38 of 0.17|2.0 refers to the single wave combination oflatency of 0.17 seconds and amplitude of 2.0 mmHg. During real-timemonitoring these numerical value combinations may be updated each timesequence 11 of 5 seconds. In one embodiment, the numerical valuecombinations 38 may be presented on the display of the apparatus, thoughthis is no limitation of the scope of the invention. For example,presentation on the display of monitoring systems is possible.

The balanced position of single wave combinations, for exampledetermined as centroid or centre of distribution, may also be presentedon the y axis in a xy chart with time on the x axis (see FIG. 8 e). Forexample, the centroid or centre of distribution of single wavecombinations may be computed repeatedly each 5 second and plotted in theXY-chart during a period of recording. In this situation, the curvereflects numerical value combinations of centroid or centre ofdistribution of single wave combinations within the histogram or matrix.

Balanced position within a matrix may have different names, such ascentroid, centre of distribution, or centre of mass. In this document itis preferred to use the term balanced position. In the context describedhere, balanced position refers to mean frequency distribution ofoccurrences of single pressure wave parameters. In this document theterms balanced position of amplitude (ΔP), balanced position of latency(ΔT) and balanced position of rise time coefficient (ΔP/ΔT) are used asterms with respect to the first and seconds matrixes, respectively.However, the term balanced position per se is a method for determiningthe mean occurrence either within a one- or two-dimensional matrix ingeneral.

With reference to the matrix presented in Table I, the procedure ofcomputing balanced position of the distribution of different amplitude(ΔP) and latency (ΔT) combinations is described. The numbers referred toin Table I relates to a recording period of 1 minute. The method ishowever, similar whether the recording period is 5, 6 or 10 seconds, or1 minute or 10 hours. The balanced position relates to the frequencydistribution of the different occurrences of amplitude (ΔP) 4 andlatency (ΔT) 5 during the selected time period. The method is similarindependent on factors such as type of pressure, group ranges, ornumbers of cells. Depending on the range of amplitude and latencyvalues, the matrixes may contain a variable number of columns and rows.However, the balanced position result is dependent on the matrixresolution.

With reference to the matrix presented in Table I, the columns refer toamplitude (ΔP) 4 groups and the rows to the latency (ΔT) 5 groups. Thesystem will have i rows, and j columns. When computing balancedposition/centroid/mean frequency of such a two-dimensional distribution(referred to as first matrix), both dimensions have to be considered.Since there are two variables the mean (or balanced position) must begiven by two numbers, like the ΔT|ΔP values. With reference to Table I,if the values from the row and column mean are considered, the resultsmay be interpreted as the mean value for the distribution. The meandistribution (or balanced position) for the numbers presented in TableI, is located in the crossing point between the two lines ΔP=1.64 andΔT=0.135. This is the most accurate way to describe the balancedposition (or mean value) for this two dimensional distribution. Thebalanced position in the matrix shown in Table I is ΔP=1.64 andΔT=0.135, corresponding to the cell with count 12. In the following,some details are given concerning computation of mean row and meancolumn values. First, the latency (ΔT) mean value (or row mean), withrespect to the amplitude (ΔP) values (columns) is determined. The m_(i)for each latency (ΔT) row is determined, by using the equation 2.$\begin{matrix}{m_{i} = {\sum\limits_{j = 1}^{j = c}{A_{j}w_{ij}}}} & (2)\end{matrix}$where A_(j) is the j^(th) column midpoint, referring to an amplitude(ΔP) group value;

w_(ij) is the frequency (count) of the i^(th) ΔT row and j^(th) ΔPcolumn cells. Then, $\begin{matrix}{{{Row}\quad{mean}} = {{{Mean}({dt})} = \frac{\sum\limits_{i = 1}^{r}{m_{i}B_{i}}}{\sum\limits_{i = 1}^{r}{m\quad i}}}} & (3)\end{matrix}$

where B_(i) is the i^(th) row ΔT midpoint value (r=row). The term“i^(th) ΔT row and j^(th) ΔP column cell” may also need an explanation.If a horizontal line is drawn through the midpoint in row i, and avertical line through the midpoint in column j, the two lines will crosseach other in a cell. This cell has the coordinates “i^(th) row andj^(th) column cell”. As an example, the data of Table I are used tocalculate the mean row value. Application of the equations (2) and (3)gives a row mean with respect to columns equal to 0.135 seconds(14.9/110.25). The calculations are shown in more detail in Table II.TABLE II Computation of row (latency) mean with respect to columns(amplitude). mi ΔTi mi × ΔTi 3 × 1.25 + 12 × 1.75 = 24.75 0.125 3.092516 × 1.25 + 12 × 1.75 + 8 × 2.25 = 59 0.135 7.965 7 × 1.25 + 5 × 1.75 +4 × 2.25 = 26.5 0.145 3.8425 Sum = 110.25 14.9Row mean: 14.9/110.25 = 0.135 secondsSecond, the ΔP mean value (columns), with respect to the ΔT value(rows), is determined. The column ΔP mean value are found using the sameapproach as used for finding the mean row ΔT value. First, the m_(j) foreach ΔP column is found, as given in equation (4). $\begin{matrix}{m_{j} = {\sum\limits_{i = 1}^{i = r}{B_{i}w_{ij}}}} & (4)\end{matrix}$where B_(i) is the i^(th) row ΔT midpoint, and referring to a ΔT groupvalue and w_(ij) is the frequency for the i^(th) row and j^(th) column.Then, $\begin{matrix}{{{Column}\quad{mean}} = {{{Mean}({dP})} = \frac{\sum\limits_{j = 1}^{j = c}{m_{j}A_{j}}}{\sum\limits_{j = 1}^{j = c}{m\quad i}}}} & (5)\end{matrix}$

where A_(j) is the j^(th) column ΔP value midpoint (c=column). Thecalculations are shown in Table III, using the equations (4) and (5),the column mean with respect to rows will be equal to 1.64 mmHg(14.9/9.055). TABLE III Computation of column (amplitude) mean withrespect to rows (latency). Column mj ΔPj mj × ΔPj 1 2 3 × 0.125 + 16 ×0.135 + 7 × 0.145 = 3.55 1.25 4.4375 3 12 × 0.125 + 12 × 12 × 0.135 +1.75 6.72875 5 × 0.145 = 3.845 4 8 × 0.135 + 4 × 0.145 + 4 ×= 1.66 2.253.735 5 Sum 9.055 14.9Column mean: 14.9/9.055 = 1.64 mmHg

Finally, it should be mentioned that balanced position may as well bedetermined within a one-dimensional matrix (termed second matrix). Sucha matrix is used for determining balanced position of occurrences ofrise-time coefficients during a given time sequence. It may be used forother one-dimensional matrix variables/relations as well. In thissituation the rise time coefficients are plotted in a one-dimensionalmatrix of pre-defined rise time coefficients. In such a one-dimensionalfrequency distribution we have two variables x_(i), and w_(i) (x_(i)equal to the value of each observation, w_(i) equal to the frequency orcount). x_(i) is comparable to ΔP/ΔT and w_(i) is comparable to thenumber of occurrences of the various ΔP/ΔT combinations. The mean ofthis distribution may be computed according to equation 6:$\begin{matrix}{{\overset{\_}{X} = \frac{\sum\limits_{i = 1}^{k}{x_{i}w_{i}}}{\sum\limits_{i = 1}^{k}w_{i}}},{k = {{number}\quad{of}\quad{observations}}}} & (6)\end{matrix}$

It has been discussed computation of a two-dimensional matrix ofcombinations of amplitude (ΔP) and latency (ΔT) combinations (referredto as the first matrix), and also computation of a one-dimensionalmatrix of combinations of rise-time coefficients (ΔP/ΔT) (referred to asthe second matrix). It should be noted that these are examples, and notintended to limit the scope of the invention. A matrix may contain anyof the single pressure wave parameters discussed in this document, andany combinations are possible. Matrixes may be computed for any type ofpressure. The numbers of groups may be selected.

Reference is now given to FIGS. 6 a-c. This figure illustratesdifferences between computation of absolute mean pressure and singlepressure wave parameters. Intracranial pressure was measuredsimultaneously by means of two different sensors located within thebrain parenchyma, separated by 1-2 centimetres. Intracranial pressurewould be expected to be similar, given the narrow location between thesensors. Intracranial pressure was measured simultaneously by the twosensors. Since measurements had identical time reference, the singlepressure wave parameters computed within given time sequences of 6seconds duration could be compared time sequence for time sequence. Foreach time sequence 11 absolute mean pressure was computed according toMetode 2, as well as balanced position of amplitude (ΔP) and balancedposition of latency (ΔT). Time sequence for time sequence in thecontinuous series of time sequences, differences between the twopressure recordings were computed with regard to absolute mean pressure(FIG. 6 a), balanced position of amplitude (ΔP) (FIG. 6 b), and balancedposition of latency (FIG. 6 c). With reference to FIG. 6 a, on the xaxis is shown the number of the time sequences 22. In this recordingperiod, the first time sequence starts with number 1 and the last timesequence ends with number 4100, indicating the start and end of therecording period, respectively. Thus, the continuous recording periodconsisted of a series of 4100 continuous time sequences 11,corresponding to 24600 seconds (6.8 hours). On the x axis is indicatedthe scale for differences in absolute mean pressure 23. The differentialpressure curve 24 shows the trend distribution of differences inabsolute pressure within identical time sequences for two pressurerecordings with different sensors. Each plot within said differentialplot 24 presents differences within identical time sequences forabsolute mean pressure, wherein differences related to pressuresmeasured by either of said two sensors. A large variation in absolutepressures is shown. For time sequence number 1000, absolute meanpressure was 20.2 mmHg for sensor 1 and 33.3 mmHg for sensor 2, with adifference in mean pressure of −13.1 mmHg. In FIG. 6 b is indicated onthe y axis differences in balanced position of amplitude (ΔP) 25 and theseries of time sequences 22 on the x axis. The differential curve ofbalanced position 26 shows for consecutive time sequences differences inbalanced position of amplitude (ΔP). The trend curve show 25 thatdifferences in balanced position of amplitude (ΔP) between identicaltime sequences are minimal. For time sequence number 1000, balancedposition of amplitude was 5.2 mmHg for sensor 1 and 5.6 mmHg for sensor2. Difference in balanced position was 0.4 mmHg. In the same way,differences in balanced position of latency are shown in FIG. 6 c. InFIG. 6 c is shown on the y axis differences in balanced position oflatency (ΔT) 27 and on the x axis the consecutive series of timesequences 22. The differential trend plot of balanced position oflatency (ΔT) 28 show minimal differences between balanced position oflatency (ΔT) for different pressure curves using different sensors withidentical time sequences. The results presented in FIG. 6 a-c suggestthat pressures are less reliably predicted by absolute mean pressure, ascompared to balanced position of amplitude (ΔP) and latency (ΔP). Againit should be noted that differences were computed on a beat to beatbasis since the time reference was identical.

With regard to time sequences, absolute mean pressure and balancedposition of either amplitude (ΔP) or latency (ΔP) are only few of manydifferent single pressure wave parameters. The various parametersrelated to single pressure waves 1 are discussed in the following. Aninventive step of this invention is to store in a database the singlepressure wave related parameters computed according to the invention.The single wave 1 related parameters relate to said time sequences 11.Before creating a database, the duration of said time sequences may beselected. The inventor suggest that the duration preferably should be of5-15 seconds duration. Specific durations of said time sequences are nota limitation. The inventor computed a database wherein time sequences of6 seconds duration were selected. Within each time sequence the singlewave related parameters may either be related to each of the individualsingle pressure waves within said time sequence, or to the group ofindividual single waves within said time sequence.

For each of the individual single pressure waves 1 within said timesequence 11, the following parameters are stored (referred to as Singlewave parameters 1-6):

-   -   1. Absolute pressure value for diastolic minimum (P_(min)) 2        value for each individual single pressure wave 1 (i.e. accepted        P_(min)/P_(max) pair) during said time sequence 11.    -   2. Absolute pressure value for systolic maximum (P_(max)) 3        value for each individual single pressure wave 1 (i.e. accepted        P_(min)/P_(max) pair) during said time sequence 11.    -   3. Absolute mean pressure for each accepted single wave 1 (i.e.        accepted P_(min)/P_(max) pair) (related to each accepted        P_(min)/P_(max) pair), that is mean pressure from P_(min) to        P_(min) (wavelength) 7 for each individual single pressure wave        1 during said time sequence 11.    -   4. Relative amplitude (ΔP) 4 pressure value for each individual        single pressure wave 1 (i.e. accepted P_(min)/P_(max) pair)        during said time sequence 11.    -   5. Relative latency (ΔT) 5 value for each individual single        pressure wave 1 (i.e. accepted P_(min)/P_(max) pair) during said        time sequence 11.    -   6. Relative rise time coefficient (ΔP/ΔT) 6 value for each        individual single pressure wave 1 (i.e. accepted P_(min)/P_(max)        pair) during said time sequence 11.

For the group of single pressure waves within said time sequence 11, thefollowing parameters are stored (referred to as time sequence parameters1-12):

-   -   1. Numbers of single waves (N_(SW)) during said time sequence.    -   2. Single pressure wave derived heart rate 16, computed as        numbers of single pressure waves 1 divided with the total        duration of wavelengths (P_(min) to P_(min)) 7 of single        pressure waves within said time sequence 11.    -   3. Single pressure wave derived heart rate 16, computed as        numbers of single pressure waves 1 divided with the duration of        said time sequence 11 wherein said single pressure waves occur.    -   4. Absolute mean pressure for said time sequence 11, computed as        the sum of absolute mean pressure (entire wavelength 7 from        P_(min) to P_(min)) for all individual single waves 1 during        said time sequence 11, divided by numbers of single waves within        said time sequence 11 (referred to as Method 2).    -   5. Standard deviation for mean pressure of mean pressure for the        individual single waves 1 occurring during said time sequence        11.    -   6. Standard deviation for diastolic minimum (P_(min)) 2 during        said time sequence, which is computed as standard deviation for        diastolic minimum (P_(min)) 2 of all individual single waves 1        during said time sequence 11.    -   7. Standard deviation for systolic maximum (P_(max)) 3 during        said time sequence 11, which is computed as standard deviation        for systolic maximum (P_(max)) 3 of all individual single waves        1 occurring during said time sequence 11.    -   8. Standard deviation for amplitude (ΔP) 4 of all individual        single pressure waves 1 occurring during said time sequence 11.    -   9. Standard deviation for latency (ΔT) 5 of all individual        single pressure waves 1 occurring during said time sequence 11.    -   10. Standard deviation for rise time coefficient (ΔP/ΔT) 6 of        all individual single pressure waves 1 occurring during said        time sequence 11.    -   11. Balanced position of amplitude (ΔP)/latency (ΔT)        combinations in said amplitude/latency matrix (referred to as        first matrix).    -   12. Balanced position of rise time coefficients (ΔP/ΔT) in rise        time coefficient matrix (referred to as second matrix).

All the single pressure wave related parameters are computed for eachtime sequence. Given that the duration of each time sequence is set to 6seconds, an individual recording of 10 hours consists of 6000 timesequences. For example, the sole parameter Balanced position ofamplitude (ΔP) and latency (ΔT) consists of two values (e.g. 0.12seconds|6.25 mmHg), that gives 12000 values during a 10 hours recordingperiod (20 values/minute×60 minutes/hr×10 hrs). These 12000 valuesinclude 6000 values of balanced position amplitude (ΔP) 4 and 6000values of balanced position latency (ΔT) 5. Thus, for every timesequence the single wave related parameters are stored. The inventorfirst created a database based on time sequences of 6 seconds. At anearly stage the database consisted of several millions of said timesequences. Since the data are continuous, it is easy to change theduration of the time sequence (e.g. to 5 seconds duration), though thecomputer requires time to process the digital data.

The database serves several purposes; an important purpose is todetermine relationships between the different single wave parameters.Since relationships between several parameters within identical timesequences may be determined, it is also possible to determine oneparameter as a function of two or more other parameters. For example,for one individual pressure recording, the single pressure waveparameters within each time sequence may be related. This procedure maybe computed in a scatter plot with one parameter on the y axis and theother on the x axis. An example is given. A continuous pressurerecording of 10 hours contains a total of 6000 time sequences, eachlasting 6 seconds. Provided that 5400 of 6000 time sequences areaccepted from said pressure recording, this pressure recording containsa total of 5400 values of balanced position of amplitude (ΔP) 4 and 5400values of latency (ΔT) 5. In a scatter plot each value refers to acombination of balanced position of amplitude (ΔP) 4 and balancedposition of latency (ΔT) 5. The relationships between the 5400 plots mayfurther be determined by computing the best fitted curve. Goodness offit may be determined by various strategies. For a given relationship,it is the experience of the inventor that the goodness of fit as well asthe spread of the plot may differ among different pressure recordings.

The relationships between parameters may as well be determined for agroup of individual pressure recordings. For example, for a group of 100individual pressure recordings the relationships between balancedpositions of amplitude (ΔP) 4 and latency (ΔT) 5 may be determined.Given that each individual pressure recording contains an average of5400 values of balanced position of amplitude (ΔP) 4 and 5400 values ofbalanced position of latency (ΔT) 5, an averaged total of 540 000 valuesof each variable is available. Various mathematical procedures arepossible to determine the relationships between these variables in sucha large sample. A scatter of 540 000 plots may be made. A relationshipmay as well be made by a random selection of the total material. Theinvention does not limit to a particular strategy for determiningrelationships within a large material, as various mathematicalstrategies are possible.

In FIGS. 7 a-c addresses the topic of determining relationships betweensingle pressure wave parameters within a group of individual pressurerecordings. This is an example of one strategy, though this example isnot intended to limit the scope of the invention. The data presented inFIGS. 6 a-c represents a total of 40 individual pressure recordings.These 40 individual pressure recordings contain a total of 330540individual time sequences 11, each lasting 6 seconds. First, eachindividual of said 40 individual pressure recordings were considered.For each individual pressure recording, the best fitted equation isdetermined for ranges of the parameters wherein the curve is based. Forexample, for one pressure recording the best fitted equation wasapplicable for the amplitude (ΔP) ranges of 2.5 to 6.7 mmHg, whereasanother pressure recording determined the best fitted equation for theamplitude (ΔP) ranges of 5.4 to 12.0 mmHg. Second, the best fittedcurves 31 from the individual pressure recordings were sampled within ascatter of all 40 individual pressure recordings. In FIG. 7 a the y axisshows the balanced position values of amplitude (ΔP) values 29, and thex axis the balanced position of latency (ΔT) 30. In FIG. 6 b is balancedposition of amplitude (ΔP) values 29 on the y axis plotted againstabsolute mean pressure (computed according to Method 2) 18 on the xaxis. In FIG. 6 a is indicated the regression line 31 corresponding toindividual pressure recordings of the relationship between balancedposition of amplitude (ΔP) and latency (ΔT). The total regression line32 for all individual pressure recordings is shown. This corresponds tothe relationship between balanced position of amplitude (ΔP) and latency(ΔT) for the whole group of 40 individual pressure recordings including330540 time sequences. The relationship is exponential. In FIG. 7 b isshown the regression lines 33 for the individual pressure recordings forthe relationship between balanced position of amplitude (ΔP) 29 andabsolute mean pressure 18. The total regression line 34 for allindividual regression lines concerning relationship between balancedposition of amplitude (ΔP) 29 and absolute mean pressure 18 is shown inFIG. 6 b. The equation of the total regression line 32 of FIG. 6 a maybe combined with the equation of the total regression line 34 of FIG. 6b. Since both equations contain the variable balanced position ofamplitude (ΔP) 29, it is possible to compute one of the variables as afunction of the others. This aspect is further illustrated in FIG. 6 c,wherein the variables balanced position of amplitude (ΔP) 29, balancedposition of latency (ΔT) 30, and absolute mean pressure 18 are plottedare plotted in a 3D graph. In FIG. 7 c is shown a graphical presentationof the three-dimensional regression line 35 based on the equation of thethree variables balanced position of amplitude (ΔP) 29, balancedposition of latency (ΔT) 30, and absolute mean pressure 18. The equationof this three-dimensional regression line shows one variable as afunction of the two other variables. Independent of the method, thefollowing model was computed for this particular relationship: Meanpressure=a+b₁×ΔP+b₂×ΔT³. On this basis an equation was determined:Predicted mean pressure=3.214+1.3×ΔP+63.609×ΔT ³   (7)

It should be noted that this equation is relevant for the data presentedin FIGS. 7 a and 7 b. For other materials, other equations may becomputed. This equation is included to give an example of how one singlepressure wave parameter may be expressed as a function of two othersingle pressure wave parameters. The data have been selectively chosen,but contains a huge number of comparisons. The data shown in thesefigures consist of 330 540 individual time sequences 11, each lasting 6seconds. Nevertheless, an important question is how to establish adatabase of individual pressure recordings that may provide a reliablerelationship between the single pressure wave parameters. According tothis invention, selected criteria are established to determine whetheror not an individual pressure recording may be included in determiningthe relationship between single pressure wave parameters. Not allscatter plots of single pressure wave parameters are useful fordetermining fitted curve formulas since the variation within the plotmay be very large. Determination of goodness of fit for regression linesof individual pressure recordings may be made by various strategies. Animportant issue is also to determine which parameters that do or do notinfluence on each other.

An important aspect of determining relationships between single pressurewave related parameters is an inventive procedure of giving weights tocells within a matrix. Reference has been made to said first matrix ofamplitude (ΔP) and latency (ΔT) combinations (see Table I). The cellswithin the matrix described in Table I may be represented as weightvalues. Instead of the word weight, the word score might be used. Inthis description the word weight is preferred. A weighted cell valuemeans that each cell in said matrix (see Table I) is represented by onevalue instead of two values corresponding to the respective column androw numbers. According to the invention, weight values are made on thebasis of observations. In this context, observations refer to therelationships established by means of the database.

Reference is now given to Table IV that is a weight matrix. The groupnames, ranges and midpoints correspond to the amplitude/latency matrixshown in Table I. For example, the amplitude (ΔP) group named 1.5 mmHgincludes amplitude values equal to or larger than 1.5 mmHg, but lessthan 2.0 mmHg, with group midpoint value equal to 1.75 mmHg. The latency(ΔT) group termed 0.11 seconds includes latency values equal to orlarger than 0.11 seconds, but less than 0.12 seconds, with groupmidpoint value of 0.115 seconds. With reference to Table IV, theequation of the relationships presented in FIG. 7 c was used to giveeach individual cell in said matrix a weight value. The weight value wasconsidered as equal to predicted mean (Predicted meanpressure=3.214+1.3×ΔP+63.609×ΔT³). The equation was applied to eachamplitude and latency group within said matrix. The equation describesthe predicted mean value as a function of the balanced position ofamplitude (ΔP) and latency (ΔT) values. With reference to Table IV, thegroup midpoint values of amplitude (ΔP) and latency (ΔT) groups wereused as input values to the equation to give each cell a predicted meanvalue. For example, by using the equation 7 related to FIG. 7 c(Predicted mean pressure=3.214+1.3×ΔP+63.609×ΔT³), the cellcorresponding to amplitude (ΔP) group 1.5 mmHg (with group midpoint 1.75mmHg) and latency (ΔT) group 0.11 seconds (with group midpoint 0.115seconds) would be represented with the predicted mean pressure value of5.59 mmHg. In this example the whole matrix is weighted according to theequation computed according to the relationships presented in FIGS. 7 ato 7 c. Based on the relationships presented in FIGS. 7 a to 7 c, it isalso possible to compute one individual equation for each amplitude (ΔP)group within said matrix. Thereby, each equation is applicable forranges of amplitude (ΔP), for example the ranges 0.5<ΔP≦1.0 mmHg.

It should be noted that the numbers and equations presented are used asillustrative examples and are not intended to limit the scope of theinvention. The weight values computed depend on the relationshipsdetermined according to the observational data. Which absolute pressurelevels that correspond to which balanced position ΔP and ΔT levelsdepend on the fitted curve equations computed for the particular dataset. The invention sets no limitations concerning which types ofobservations the relationships are based on. Preferentially the plotsshould be based on a group of patients. However, separate plots may bemade for different patient groups, patient ages, and disease states.These curves may to some extent differ depending on the types ofpressures measured, compartments where pressures are measured, method bywhich pressures are measured, age of patient in whom pressures aremeasured, as well as disease state of the patient. In these situationscertain weight matrixes may be used only for particular patient groupsor disease states. TABLE IV A part of a weight matrix wherein the numberin each matrix cell is a weight value that is a function of theamplitude (dP) and latency (dT) values. Group name 0.5 1 1.5 2 2.5 Grouprange 0.5 < dP < 1.0 1.0 < dP < 1.5 1.5 < dP < 2.0 2.0 < dP < 2.5 2.5 <dP < 3.0 Group midpoint 0.75 1.25 1.75 2.25 2.75 0.1 0.10 < dT < 0.110.105 4.26 4.91 5.56 6.21 6.86 0.11 0.11 < dT < 0.12 0.115 4.29 4.945.59 6.24 6.89 0.12 0.12 < dT < 0.13 0.125 4.31 4.96 5.61 6.26 6.91 0.130.13 < dT < 0.14 0.135 4.35 5.00 5.65 6.30 6.95 0.14 0.14 < dT < 0.150.145 4.38 5.03 5.68 6.33 6.98 0.15 0.15 < dT < 0.16 0.155 4.43 5.085.73 6.38 7.03 0.16 0.16 < dT < 0.17 0.165 4.47 5.12 5.77 6.42 7.07 0.170.17 < dT < 0.18 0.175 4.53 5.18 5.83 6.48 7.13 0.18 0.18 < dT < 0.190.185 4.59 5.24 5.89 6.54 7.19 0.19 0.19 < dT < 0.20 0.195 4.66 5.315.96 6.61 7.26 0.2 0.20 < dT < 0.21 0.205 4.74 5.39 6.04 6.69 7.34 0.210.21 < dT < 0.22 0.215 4.82 5.47 6.12 6.77 7.42 0.22 0.22 < dT < 0.230.225 4.91 5.56 6.21 6.86 7.51 0.23 0.23 < dT < 0.24 0.235 5.01 5.666.31 6.96 7.61 0.24 0.24 < dT < 0.25 0.245 5.12 5.77 6.42 7.07 7.72 0.250.25 < dT < 0.26 0.255 5.24 5.89 6.54 7.19 7.84 0.26 0.26 < dT < 0.270.265 5.37 6.02 6.67 7.32 7.97 0.27 0.27 < dT < 0.28 0.275 5.51 6.166.81 7.46 8.11 0.28 0.28 < dT < 0.29 0.285 5.66 6.31 6.96 7.61 8.26 0.290.29 < dT < 0.30 0.295 5.82 6.47 7.12 7.77 8.42 0.3 0.30 < dT < 0.310.305 5.99 6.64 7.29 7.94 8.59 0.31 0.31 < dT < 0.32 0.315 6.18 6.837.48 8.13 8.78 0.32 0.32 < dT < 0.33 0.325 6.37 7.02 7.67 8.32 8.97 0.330.33 < dT < 0.34 0.335 6.58 7.23 7.88 8.53 9.18 0.34 0.34 < dT < 0.350.345 6.80 7.45 8.10 8.75 9.40 0.35 0.35 < dT < 0.36 0.355 7.03 7.688.33 8.98 9.63 0.36 0.36 < dT < 0.37 0.365 7.28 7.93 8.58 9.23 9.88 0.370.37 < dT < 0.38 0.375 7.54 8.19 8.84 9.49 10.14 0.38 0.38 < dT < 0.390.385 7.82 8.47 9.12 9.77 10.42 0.39 0.39 < dT < 0.40 0.395 8.11 8.769.41 10.06 10.71 0.4 0.40 < dT < 0.41 0.405 8.41 9.06 9.71 10.36 11.01Group name 3 3.5 4 4.5 5 Group range 3.0 < dP < 3.5 3.5 < dP < 4.0 4.0 <dP < 4.5 4.5 < dP < 5.0 5.0 < dP < 5.5 Group midpoint 3.25 3.75 4.254.75 5.25 0.1 0.10 < dT < 0.11 0.105 7.51 8.16 8.81 9.46 10.11 0.11 0.11< dT < 0.12 0.115 7.54 8.19 8.84 9.49 10.14 0.12 0.12 < dT < 0.13 0.1257.56 8.21 8.86 9.51 10.16 0.13 0.13 < dT < 0.14 0.135 7.60 8.25 8.909.55 10.20 0.14 0.14 < dT < 0.15 0.145 7.63 8.28 8.93 9.58 10.23 0.150.15 < dT < 0.16 0.155 7.68 8.33 8.98 9.63 10.28 0.16 0.16 < dT < 0.170.165 7.72 8.37 9.02 9.67 10.32 0.17 0.17 < dT < 0.18 0.175 7.78 8.439.08 9.73 10.38 0.18 0.18 < dT < 0.19 0.185 7.84 8.49 9.14 9.79 10.440.19 0.19 < dT < 0.20 0.195 7.91 8.56 9.21 9.86 10.51 0.2 0.20 < dT <0.21 0.205 7.99 8.64 9.29 9.94 10.59 0.21 0.21 < dT < 0.22 0.215 8.078.72 9.37 10.02 10.67 0.22 0.22 < dT < 0.23 0.225 8.16 8.81 9.46 10.1110.76 0.23 0.23 < dT < 0.24 0.235 8.26 8.91 9.56 10.21 10.86 0.24 0.24 <dT < 0.25 0.245 8.37 9.02 9.67 10.32 10.97 0.25 0.25 < dT < 0.26 0.2558.49 9.14 9.79 10.44 11.09 0.26 0.26 < dT < 0.27 0.265 8.62 9.27 9.9210.57 11.22 0.27 0.27 < dT < 0.28 0.275 8.76 9.41 10.06 10.71 11.36 0.280.28 < dT < 0.29 0.285 8.91 9.56 10.21 10.86 11.51 0.29 0.29 < dT < 0.300.295 9.07 9.72 10.37 11.02 11.67 0.3 0.30 < dT < 0.31 0.305 9.24 9.8910.54 11.19 11.84 0.31 0.31 < dT < 0.32 0.315 9.43 10.08 10.73 11.3812.03 0.32 0.32 < dT < 0.33 0.325 9.62 10.27 10.92 11.57 12.22 0.33 0.33< dT < 0.34 0.335 9.83 10.48 11.13 11.78 12.43 0.34 0.34 < dT < 0.350.345 10.05 10.70 11.35 12.00 12.65 0.35 0.35 < dT < 0.36 0.355 10.2810.93 11.58 12.23 12.88 0.36 0.36 < dT < 0.37 0.365 10.53 11.18 11.8312.48 13.13 0.37 0.37 < dT < 0.38 0.375 10.79 11.44 12.09 12.74 13.390.38 0.38 < dT < 0.39 0.385 11.07 11.72 12.37 13.02 13.67 0.39 0.39 < dT< 0.40 0.395 11.36 12.01 12.66 13.31 13.96 0.4 0.40 < dT < 0.41 0.40511.66 12.31 12.96 13.61 14.26

In FIG. 8 is illustrated how determination of single wave distributionmay be used in the real-time and online monitoring of pressures. Thefirst sequence of events is indicated in FIGS. 8 a to 8 c, providing aschematic overview of computing balanced position of amplitude/latencycombinations within consecutive time sequences 11. Pressure signals fromany type of pressure sensor may be sampled, and the single waves 1identified. Within each time sequence 11 (illustrated with a duration of5 seconds; FIG. 8 a), the single pressure waves 1 are identified. InFIG. 8 a is indicated seven single pressure waves within the timesequence 11 of 5 seconds. For all accepted single pressure waves 1within said time sequence 11, the single pressure wave parametersamplitude (ΔP) 4 and latency (ΔT) 5 are plotted in a first matrix 36.The first matrix 36 in FIG. 8 b represents only a small part of a matrix36 for intracranial pressure. The numbers 37 presented in the matrix arenumbers of single waves with different combinations of latency 5 andamplitude 4 during said time sequence 11. An alternative to presentingnumbers is presentation of percentages of combinations. With referenceto FIG. 8 b, the numbers of occurrences of single waves with amplitudeof 2.0 mmHg and a latency of 0.13 seconds was 2 during said timesequence of 5 seconds. For this matrix 36 the numerical value 38 ofbalanced position of amplitude and latency combinations was 0.12seconds|2.4 mmHg (FIG. 8 c). This combination of 0.12|2.4 refers to thesingle pressure wave combination wherein latency 5 was 0.12 seconds andamplitude 4 2.4 mmHg. In fact, various terms may be used concerningbalanced position such as centre of mass or centroid. In this context,the balanced position refers to the mean frequency distribution ofamplitude 4 and latency 5 combinations within said time sequence 11 andrepresented in said matrix 36, as previously described in detail. Theprocedure in FIG. 8 a-c is repeated every new time sequence 11 in thecontinuous series of time sequences 11 during a continuous pressuremonitoring. Accordingly a new balanced position is computed each new 5seconds in this particular example. During real-time monitoring thesenumerical value combinations may be updated each 5 seconds. Thenumerical value combinations 38 may be presented on the display of anapparatus or a monitor.

During on-line monitoring it may be difficult for the physician or nurseto relate to new numerical values presented each 5 seconds. Therefore,various examples of presentations are given in FIG. 8 d-f. In all theseexamples the two-dimensional values of balanced position are presentedas one-dimension values. According to this invention this is madepossible by weighting of the matrix cells. Thereby, the two-dimensionalbalanced position may be represented by a one-dimensional weightedvalue. In FIG. 8 d is shown a histogram presentation with numbers orproportions 39 on the y axis and weighted balanced position 40 values onthe x axis. For example, such a histogram may reveal for a givenrecording period the total distribution of weighted values of balancedpositions 40 of amplitude and latency within the time sequencesoccurring during said recording period, as further shown in FIGS. 9 b, 9d, 10 b, and 10 d. In such a histogram each bar 41 represents a givenweighted value of balanced position of amplitude and latency within said5-second time sequences, with the numbers or proportions of saidweighted values represented on the x axis. In FIG. 8 e is presentedweighted values of balanced position 40 of amplitude/latencycombinations in a trend plot, with time scale 12 on the x axis andweighted values of balanced position 40 on the y axis. In the trend plot42 each plot represents a weighted value of balanced position 40 ofamplitude and latency within a time sequence of 5 seconds. Thus, thetrend plot shows the output of analysis of each time sequence in acontinuous series of time sequences. Criteria may be selected forhandling excluded time sequences. Examples of trend plots 42 of weightedvalues are further given in FIGS. 11 b and 11 d. A third alternative ofpresenting single wave distribution is indicated in FIG. 8 f. Amodification of a so-called pressure volume curve may be computed for alarge number of individuals. Such a curve may depend on age. Theinventor has computed so-called pressure volume curves for adults bymeans of so-called infusion tests, previously described in U.S. patentapplication Ser. No. 09/843,702 and International Patent ApplicationPCT/NO 02/00164. On the X-axis is indicated change of volume 43. On theY-axis is indicated the balanced position 40 of amplitude and latency.During so-called infusion tests a fixed volume is applied to theintracranial compartment, for example with similar volume changes each 5seconds. During each 5 seconds the single waves are monitored withcomputation of matrix 36. The balanced position 40 may be computed, andexpressed on the Y-axis. The fixed volume change 43 is indicated on theX-axis. The inventor has been able to compute such pressure volumecurves for a large number of patients. Thereby reference curves havebeen computed, indicating both normal and abnormal curves. Suchreference curves may be shown on the display of the apparatus or onother monitor systems. During real-time monitoring the balanced positionof single wave combinations may be plotted in relation to the modifiedpressure volume curve, for example each 5 seconds. Thereby, real-timeand online update of balanced position for a single case may be computedreal-time and online and related to a reference curve. Therebyinformation about compliance/elastance is obtained.

Reference is now given to FIG. 9 that shows two different intracranialpressure recordings in one single case. Pressures were recordedsimultaneously (with identical time reference) by means of one sensorplaced within the brain parenchyma (FIGS. 9 a-9 b) and one sensor placedepidurally (FIGS. 9 c-9 d). An epidural placement means that the sensoris placed outside the dura mater actually mimicking non-invasivepressure monitoring since the sensor is not placed within the cavity inwhich pressure is measured. Both pressures measured within brainparenchyma and epidurally are relative to atmospheric pressure, andrepresent absolute pressures. For both pressure curves (FIGS. 9 a and 9c) are presented the absolute pressures 17 on the y axis and the timescale 12 on the x axis. Both the x axes show identical time sequences,making a beat to beat comparison possible. It should be noted that theabsolute pressures differ for the pressure curve 21 for parenchyma (FIG.9 a) and epidural (FIG. 9 c) pressures. For FIG. 9 a mean intracranialpressure for the whole recording period was 5.9 mmHg. For FIG. 9 c meanintracranial pressure for the whole recording period was 8.35 mmHg. Inthis context, the absolute mean pressure values of 5.9 and 8.35 mmHgactually represent the mean of all 5 second time intervals during thetotal recording period. On the other hand, the distribution of singlewaves was nearly identical between parenchyma and epidural measurements,as indicated in the histogram located to the right for each pressurecurve (FIGS. 9 b and 9 d). Whereas the pressure curves 21 show absolutepressures the histograms refer to single waves defined by relativepressures. The amplitudes of the single waves are computed as relativepressure differences. In FIGS. 9 b and 9 d is shown the histogramwherein all weighted values 40 of balanced positions of amplitude andlatency during said recording period is shown on the x axis. On the yaxis the percentage occurrence 39 is indicated, which is how often asingle wave with a certain combination of latency/amplitude occurs inpercentage of the total number of single waves during the recordingperiod. Each balanced position of amplitude/latency combinationsrepresented by a weight value is represented by one bar 41 in thehistogram. For example, the label on the X-axis of 0.38|6.50 refers tosingle waves with a combination of latency of 0.38 seconds and amplitudeof 6.50 mmHg. In this example the values 0.31|5.00, 0.38|6.50 and0.14|8.50 refer to balanced position values. These values might as wellbe referred to as index values when a weighted matrix is used. Thehistograms presented in FIG. 9 b and 9 d actually show weighted balancedposition values 40 of all time sequences 11 during the recording periodillustrated in FIGS. 9 a and 9 c. The bar corresponding to thelatency|amplitude combination of 0.38|6.50 indicates the percentage bywhich single wave occurred as related to the total numbers of singlewaves. For parenchyma (FIG. 9 b) and epidural (FIG. 9 d) pressures, thesingle wave distribution is nearly identical. These pressure recordingsillustrate several important aspects of the invention: Absolutepressures recorded by the conventional strategy and illustrated in thepressure curves give no reliable description of the pressures. Pressureswithin the brain parenchyma and the epidural space as revealed by thepressure curves were markedly different. Both the absolute pressures andthe morphology of the curve were different. Continuous pressurerecordings are most accurately described by the single wavedistribution. The histogram presentations of the single wavedistribution were nearly identical for pressure recordings within thebrain parenchyma and the epidural space. Therefore, single wavedistribution may be equally presented whether or not the sensor isplaced within the cavity pressure is measured. Results such as thesegave the idea to compute single wave distribution in infants bymonitoring fontanel pressure non-invasively by applying a sensor on thefontanel. When the results presented in FIGS. 9 a-d are presented in adifferential plot as described in FIGS. 6 a-c, absolute mean pressure iscompared time sequence for time sequence. Also balanced position ofamplitude and latency is compared time sequence for time sequence, sinceboth pressure curves have identical time reference. Such a differentialplot of the results presented in FIGS. 9 a-d showed a marked differencein absolute mean pressures between parenchymatous and epiduralmeasurements. The differences in balanced positions of amplitude andlatency between time sequences with identical reference were minimal.

Reference is now given to FIGS. 10 a-d illustrating how matrix andhistogram presentations change before and after intervention in onesingle case. With reference to the first recording period, is presentedthe pressure curve 21 (FIG. 10 a) and histogram (FIG. 10 b). The trendplot 21 (FIG. 10 c) and histogram (FIG. 10 d) for the second recordingperiod also is presented. The matrix 36 corresponding to FIGS. 10 a and10 b is shown in Table V, and the matrix 36 corresponding to FIGS. 10 cand 10 d in Table VI. An explanation of the different amplitude 4 andlatency 5 groups presented in Tables V and VI are further given forTable I. The numbers 37 within cells of matrix 36 presented in Table Irepresent absolute numbers, whereas the numbers in Tables V and VI referto percentages. Before intervention, the combination of amplitude 4 of7.5 mmHg and latency 5 of 0.26 seconds occurred in 0.17% of the totalnumbers of single waves. After intervention, the combination ofamplitude 4 of 7.5 mmHg and latency 5 of 0.26 seconds did not occur. Inthis particular example, the matrixes 36 including amplitudes 4 andlatencies 5, were standardized to a recording period and a heart rate.Non-standardized numbers may as well be presented. The standardizedrecording period was set to one hour. The actual heart rate was variableduring the recording period, but was standardized to a standardizedheart rate of 70 beats a minute. With reference to histograms (FIG. 10c, 10 d), on the y axis is shown percentage of occurrence 39 that is howoften a single wave with a certain latency|amplitude combinationoccurred in percentage of the total number of single waves. On the xaxis is shown the different weighted latency|amplitude combinations 40.As an example; in these histograms the label 0.14|8.50 on the x axisrefers to single waves with latency 5 of 0.14 seconds and amplitude 4 of8.50 mmHg. Accordingly, the bar 41 corresponding to the label 0.14|8.50shows the percentage of single waves with this combination occurring aspercentage of total number of single waves during a standardizedrecording time of one hour and a standardized heart rate of 70 beats aminute. Before (FIGS. 10 a, 10 b) and after (FIGS. 10 c, 10 d)intervention, the matrixes (Tables V and VI) and histograms showed amarked difference in single wave distribution, with a change of thesingle wave distribution in a more normal direction.

FIG. 10 also may serve as an example of distribution of balancedpositions of amplitude and latency combinations 39 for a whole recordingperiod, wherein the total distribution is presented in matrixes inTables V and VI. Thereby, balanced positions of amplitude/latencycombinations within individual time sequences for the total recordingperiod are presented as numbers in proportion 38 of the total number. Inthis situation, the bars 41 shown in the histogram refer to balancedpositions of amplitude/latency combinations during selected timesequences 11. The histograms in FIGS. 10 b and 10 d illustrate howbalanced position of amplitude and latency changes from one pressurerecording to another. With reference to the matrix in Table V, balancedposition of latency/amplitude combinations of 0.24 seconds|4 mmHgoccurred in 5.02% in the matrix 36 presented in Table V, whereas thiscombination did not occur in matrix of Table VI. In this context, itshould be noted that the matrixes 36 usually are computed each timesequence 11 with determination of balanced position of amplitude/latencycombinations for each individual time sequence 11 in a series ofcontinuous time sequences. The matrixes 36 presented in Tables V and VI,on the other hand, show the distribution of balanced positions ofamplitude and latency combinations for the whole recording period. TABLEV Matrix of amplitude (dP) and latency (dT) combinations correspondingto continuous pressure recordings presented in FIGS. 10a and 10b. dP dT1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 0.1 0.02 0.05 0.21 0.13 0.11 0.090.05 0.12 0.13 0.01 0.02 0.04 0.14 0.01 0.15 0.16 0.17 0.03 0.34 0.050.02 0.18 0.01 0.33 0.19 0.04 0.19 0.2 0.01 0.26 0.65 0.9 0.11 0.21 0.140.71 1.51 0.58 0.21 0.12 0.02 0.22 0.23 0.41 1.55 4.5 3.93 2.59 1.010.39 0.17 0.04 0.01 0.24 0.37 1.93 3.83 5.95 5.02 3.32 1.92 1.13 0.50.29 0.25 0.26 0.18 1.78 4.22 7.59 9.75 7.05 3.36 1.95 1.03 0.52 0.270.03 0.35 1.08 2.32 3.66 2.81 1.36 0.88 0.32 0.2 0.28 0.04 0.03 0.060.26 0.4 0.47 0.3 0.2 0.06 0.03 0.29 0.01 0.01 0.01 0.01 0.3 0.01 0.310.32 0.01 0.01 0.33 0.34 0.01 dP dT 7 7.5 8 8.5 9 9.5 10 10.5 11 0.10.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.2 0.21 0.22 0.23 0.040.03 0.03 0.24 0.23 0.13 0.18 0.13 0.06 0.01 0.25 0.26 0.23 0.17 0.110.07 0.06 0.09 0.05 0.03 0.02 0.27 0.1 0.05 0.01 0.02 0.01 0.01 0.280.04 0.01 0.29 0.3 0.31 0.32 0.33 0.34

TABLE VI Matrix of amplitude (dP) and latency (dT) combinationscorresponding to continuous pressure recordings presented in FIGS. 10cand 10d. dP dT 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9 9.5 1010.5 11 0.1 10.5 14.6 0.63 0.11 0.02 2.04 2.75 0.07 0.12 0.13 1.17 2.080.11 0.14 0.01 1.17 2.72 0.23 0.15 0.16 0.73 1.5 0.05 0.17 0.02 6.7411.8 0.3 0.03 0.18 5.29 5.54 0.31 0.19 0.2 0.01 3.64 7.26 0.63 0.04 0.210.82 2.17 0.34 0.03 0.01 0.22 0.23 0.79 2.6 1.38 0.13 0.05 0.24 0.21 10.91 0.12 0.01 0.25 0.26 0.11 0.73 1.42 0.36 0.06 0.27 0.04 0.54 0.910.28 0.07 0.01 0.28 0.34 0.61 0.39 0.05 0.01 0.01 0.29 0.07 0.12 0.120.04 0.01 0.3 0.07 0.06 0.04 0.01 0.31 0.32 0.02 0.09 0.05 0.04 0.330.02 0.05 0.1 0.03 0.34 0.07 0.18 0.35 0.02 0.13 0.36 0.02 0.12 0.370.02

Reference is now given to FIG. 11. Two continuous intracranial pressurecurves 21 are shown in FIGS. 11 a and 11 c. On the y axis is the scaleof absolute mean pressure 17 computed according to conventionaltechnology (Method 1). The time scale 12 is on the x axis. The trendcurve 21 presents a continuous plot of mean pressures wherein meanpressure is computed each time sequence (6 seconds duration in thiscase) in a continuous series of time sequences. Mean pressures 21 aremuch higher in FIG. 11 a than in FIG. 11 c. Below the absolute pressurecurves 21 (FIGS. 11 a and 11 c) is shown the corresponding trend plot 42of balanced position of amplitude and latency computed each 6 seconds.The two-dimensional balanced position has been computed as aone-dimensional value, as described for Table IV. By applying theequation (no. 7) used to weight the matrix 36 presented in Table IV,each balanced position of amplitude 4 and latency 5 was expressed as aweight value. The weighted value is given the term predicted meanpressure 40, shown on the y axis of FIGS. 11 b and 11 d. The time scales12 are identical for FIGS. 11 a and 11 b, and for 11 c and 11 d. Thus,the trend plots 42 of weighted balanced positions (predicted meanpressure) show balanced position of amplitude 4 and latency 5 computedeach time sequence 11 (6 seconds) that is expressed as a weighted valuestermed predicted mean pressure 40. Each plot in said trend plot 42represents the balanced position each time sequence 11 in a continuousseries of time sequences. The trend plots 42 of weighted balancedpositions are similar for FIGS. 11 b and 11 d. Thus, though absolutemean pressure curves 21 differed markedly, weighted trend plots 42 ofbalanced position did not differ. The trend plots 42 of weightedbalanced position in FIGS. 11 b and 11 d correspond to the trend plot 42schematically presented in FIG. 8 e. The histograms presented in FIGS. 9c, 9 d, 10 b, and 10 d showing weighted balanced position 40 on the xaxis correspond to the histogram presentation shown in FIG. 8 d. In boththe trend plots and histograms weighted values 40 of balanced positionof amplitude 4 and latency 5 are presented. These are examples ofpresentations and are not intended to limit the scope of the invention.

Reference is now given to FIG. 12. The present invention uses the methodfor analysis of single pressure waves 1 to provide a strategy for moreoptimal single pressure wave detection, particularly when non-invasivedevices are used for pressure monitoring. A schematic representation isprovided in FIG. 12 a. The invention may be used in conjunction withvarious types of sensors 46 providing signals indicative of pressure.The sensor device itself is not a part of the invention. It is wellknown from the prior art that sensors 46 operate together with pressuretransducers 47. An excitation signal is applied from the transducer 47to the sensor 46, and the sensor 46 gives back a new signal indicativeof the pressure to the transducer 47. The transducer 47 then processesthe signal to another signal that is more suitable for further signalprocessing. The sensor device may as well incorporate asensor-regulating device 48 that regulates how the sensor 46 is appliedto the object wherein pressure is measured. In general terms, the sensordevice consists of a sensor 46, transducer 47 and sensor-regulatingdevice 48. The pressure signals from the pressure transducer 47 arefurther converted into pressure-related digital data with a timereference, and analysed according to the invention within the processingunit 49. The method for analysis of single pressure waves provides anoutput that gives a first control signal 50 to a regulator device 52.Said regulator device may be a transducer that converts the firstcontrol signal 50 from the processing unit 49 into another secondcontrol signal 51. The second control signal 51 produced by theregulator 52 modifies the performance of the sensor-regulating device48. The sensor-regulating device modifies the mode by which thesensor/transducer is able to sample signals indicative of pressure.Thereby, the inventive method for analysis of single pressure waves isused to control and modify the sampling mode of signals derivable from apressure sensor device.

Though the sensor device itself is not a part of the invention, nor amethod by which such a sensor device is used on an animal or human bodycavity, some examples are given to illustrate the concept, though thisrepresents no limitation of the scope of the invention. First,applanation tonometry are widely used for non-invasive pressuremeasurement. Pressure gradients exist across the walls of a pressurisedelastic sphere. When a pressure sensor is applied to the surface of theflattened area, no pressure gradient exists over the flattened portion.Pressure measurements can be made when a constant pressure is applied tothe flattened area. Applanation tonometry may for example be used innon-invasive blood pressure monitoring, monitoring of ocular pressure(i.e. pressure within the ocular bulb), and even monitoring fontanelpressure in infants with an open fontanel. The pressure sensor 46consists of the pressure element that is in contact with the skin or eyebulb. Signals from the sensor 46 are converted within the pressuretransducer 47. When pressures are measured using the principles ofapplanation tonometry, it is well known that the pressure pulsation'sdetected by the tonometer depend on the pressure by which the tonometeris applied to the measurement surface. With increasing pressure from thetonometer, pressure waves increase until the waves with highestamplitudes are recorded. The pressure by which the applanation tonometryis applied to the surface determines quality of signal detection.Therefore, devices for applanation tonometry may include asensor-regulating device 48, which controls the pressure by which thetonometer is applied to the surface. Such a sensor-regulating device 48may be an inflatable balloon housed in a solid frame, under control of apneumatic system. Such a sensor-regulating device 48 provides theopportunity for controlled inflation of air into an air chamber of thesensor. The pneumatic system is automatic and controlled by a processingunit 49, in the way that the air chamber pressure is automaticallyregulated to show the best single pressure waves. Other sensors 46 applyDoppler signals to detect pressure related signals. The signal detectedby the Doppler may be modified within the transducer 47. In such asystem the sensor-regulating device 48 incorporates a system whereinDoppler signals are applied to/receive from the object, includingacquisitions of direction of signal emission as well as the signalquantity and quality. The emission and detection of Doppler signalsheavily depend on the angulations of the signal emitting source. In thissituation the sensor-regulating device 48 determines how Doppler signalare applied to the object, including acquisitions of signal directionand strength. When the sensor 46 and transducer 47 use acoustic signalsthe sensor-regulating device 48 may as well control signal direction andsignal quantity and quality. Since the sensor device itself is not aparticular feature of the invention, a more detailed description is notgiven.

The procedure for controlling and changing the sampling mode of signalsderivable from a pressure sensor device is further illustrated in FIGS.12 b and 12 c. The digital signals are sampled and analysed during shorttime sequences 11 (e.g. of 3 seconds duration) in a continuous series ofshort time sequences 11. Said analysis of single wave 1 relatedparameters within said time sequences 11 is performed by a processingunit 49. For each time sequence 11 a number of single pressure wave 1related parameters are computed, as already described in more detail.One or more of the following parameters are included:

-   (1) absolute mean pressure for each identified single pressure wave    1 [wavelength 7 (P_(min)−P_(min))] within said time sequence 11;-   (2) mean of mean pressure for all identified single pressure waves 1    [wavelength 7 (P_(min)−P_(min))] within said time sequence 11;-   (3) standard deviation of absolute mean pressure for all identified    single pressure waves 1 [wavelength 7 (P_(min)−P_(min))] within said    time sequence 11;-   (4) numbers of single pressure waves 1 during said time sequence 11;-   (5) single pressure wave derived heart rate 16 during said time    sequence 11;-   (6) relative pressure amplitude (ΔP) 4 value for each identified    single pressure wave 1 [wavelength 7 (P_(min)−P_(min))] within said    time sequence 11;-   (7) standard deviation of relative pressure amplitude (ΔP) 4 values    for all identified single pressure waves 1 [wavelength 7    (P_(min)−P_(min))] within said time sequence 11;-   (8) relative latency (ΔT) 5 value for each identified single    pressure wave 1 [wavelength 7 (P_(min)−P_(min))] within said time    sequence 11;-   (9) standard deviation of relative latency (ΔT) 5 values for all    identified single pressure waves 1 [wavelength 7 (P_(min)−P_(min))]    within said time sequence 11;-   (10) rise time (ΔP/ΔT) coefficient 6 for each identified single    pressure wave 1 [wavelength 7 (P_(min)−P_(min))] within said time    sequence 11;-   (11) standard deviation of rise time (ΔP/ΔT) coefficient 6 for all    identified single pressure waves 1 [wavelength 7 (P_(min)−P_(min))]    within said time sequence 11;-   (12) relative latency (ΔT) 5 value for each identified single    pressure wave 1 [wavelength 7 (P_(min)−P_(min))] within said time    sequence 11;-   (13) balanced position within said first matrix 36 for combinations    of single pressure wave amplitude (ΔP) 4 and latency (ΔT) 5 values    within said time sequence 11; and-   (14) balanced position within said second matrix 36 for combinations    of single pressure wave rise-time (ΔP/ΔT) 6 coefficients within said    time sequence 11.

FIG. 12 b illustrates seven time sequences 11 (1^(st), 2^(nd), 3^(rd),4^(th), 5^(th), 6^(th), and 7^(th)) where single pressure wave 1detection is modified. Single pressure wave 1 detection is most optimalduring the 3^(rd) and 4^(th) time sequences wherein the amplitudes 4 aremost evident. For each time sequence 11 said analysis procedure isapplied to all single pressure waves 1. Selected criteria are applied tothe analysis output, and would reveal most optimal single wave detectionfor the 3^(rd) and 4^(th) time sequences 11 in this example.

The output of said analysis within the processing unit 49 establishes oramends a first control signal 50 that is applied to a regulator 52. Themode of the first control signal 50 is determined by the output of saidsingle pressure wave related analysis. Between each new time sequence, afirst control signal 50 may be determined, depending on criteria appliedto the analysis results. The first control signal 50 is converted withina regulator 52. The regulator 52 may be considered as a transducerconverting the first control signal 50 into another second controlsignal 51. The regulator 52 deliverable second control signal 51 maydepend on the type of sensor-regulating device 48 incorporated in thesensor device. Therefore, the deliverable second control signal 51 maymodify a sensor-regulating device 48 in a wide sense. An example isgiven with reference to applanation tonometry wherein a pneumatic systemcontrols the pressure by which the sensor 46 is applied to the surface.The second control signal 51 delivered from the regulator 52 maydetermine the pressure level within the pneumatic system, whichdetermines the pressure by which the tonometer is applied to thesurface. This example is further illustrated in FIG. 12 c. In thissituation, the control signal level 53 determines the pressure levelwithin a pneumatic system. The pressure level 54 is increased for eachnew of the first three time sequence 11 (1^(st), 2^(nd), and 3^(rd) timesequence). As indicated in FIG. 12 b, single pressure wave 1 detectionis improved for each new of said time sequences 11. The control signallevel 53 and accordingly the pressure level 54 is kept constant betweenthe 3^(rd) and 4^(th) time sequences 11 (FIG. 12 c) wherein single waves1 remain more or less unchanged. The control signal level 53 andaccompanying pressure level 54 is reduced during the subsequent 5^(th),6^(th), and 7^(th) time sequences 11, wherein also single wave 1detection is reduced. The second control signal 51 produced by theregulator 52 may as well control a sensor regulating device 48 usingDoppler signals. In this situation the second control signal 51 maycontrol the angulations and signal quality and quantity of thesensor-regulating device 48 using Doppler signals. Furthermore, when asensor device utilizes acoustic signals, the second control signal 51may control the sensor regulating device 48 determining the quality andquantity of acoustic signals applied to the surface wherein pressuresare measured.

The results of said single pressure wave 1 analysis are compared fordifferent time sequences 11. Changes in a first control signal 50 andsubsequent in another second control signal 51 both producemodifications of the sensor-regulating device 48. The deliverablecontrol signals corresponding to analysis output wherein single pressurewave parameters meet one or more selectable criteria would be usedduring subsequent pressure monitoring. The selectable criteriacorrespond to the control signal wherein the most optimum singlepressure wave detection is obtained.

It is not within the scope of the invention to limit the strategy bywhich the process is performed. The system provides feedback interactionbetween the processing unit 49 performing said analysis, the deliverablefirst control signal 50 to the regulator 52 controlling and changing thedeliverable second control signal 51 applied to the sensor-regulatingdevice 48. It is described one example of the interactive operation ofthe regulator 52 and processing unit 49 related to the description shownin FIGS. 12 b and 12 c, though this represents no limitation of thescope of the invention. During a given time period of for example 30seconds, the regulator 52 delivers a total of ten different secondcontrol signals 51, each separated by 3 seconds. During the period of 30minutes, ten modifications of the sensor-regulating device 48 are madebetween each of said 3 second intervals. During the ten time sequences11 (each lasting 3 seconds), single pressure waves are analyzed withinthe processing unit 49. For each of said time sequences 11 the output ofthe analysis within the processing unit 49 determines a first controlsignal 50 that corresponds to the second control signal 51 from theregulator 52. Accordingly, each time sequence 11 corresponds to a secondcontrol signal 51 from said regulator 52 that corresponds to an outputof single pressure wave 1 analysis within said processing unit 49 thatfurther corresponds to a first control signal 50 to the regulator 52.These corresponding values are determined for each individual of the tentime sequences 11 during said recording period of 30 minutes. During thesubsequent pressure monitoring, the processing unit 49 provides thefirst control signal 50 that corresponds to optimum single pressure wave1 detection. This first control signal 50 from the processing unit 49 tothe regulator 52 gives another second control signal 51 to thesensor-regulating device 48, further enabling the sensor-regulatingdevice 48 for optimum single pressure wave 1 detection. The procedure ofdetermining the most optimum control signal (here exemplified as lasting30 minutes) may be reiterated at selected intervals during an ongoingpressure measurement. Various modifications of this process arepossible. For example, during an ongoing pressure monitoring theprocessing unit 49 may automatically determine the second control signal51 from the regulator 48, wherein single pressure wave 1 detection ismost optimum.

1. A method for analyzing pressure signals derivable from pressuremeasurements on or in a body of a human being or animal, comprising thesteps of sampling said signals at specific intervals, and convertingthus sampled pressure signals into pressure-related digital data with atime reference, wherein for selectable time sequences the methodcomprises the further steps of: a) identifying from said digital datasingle pressure waves related to cardiac beat-induced pressure waves, b)computing time sequence parameters of said single pressure waves duringindividual of said time sequences, and c) establishing an analysisoutput selected from one or more of said time sequence parameters ofsaid single pressure waves during individual of said time sequences: c1)balanced position of amplitude (ΔP)/latency (ΔT) combinations, c2)balanced position of rise time coefficients (ΔP/ΔT), c3) absolute meanpressure for said single pressure waves of said time sequence.
 2. Amethod according to claim 1, wherein each of said selectable timesequences is a selected time duration of said pressure-related digitaldata with a time reference.
 3. A method according to claim 2, whereinsaid selected time duration lies in the range 5-15 seconds.
 4. A methodaccording to claim 1, wherein the method is applied to each of saidselectable time sequences in a continuous series of said time sequencesduring a recording.
 5. A method according to claim 1, wherein saididentifying step a) includes identification of peaks and valleys in saidsampled signal.
 6. A method according to claim 5, wherein all minimumand maximum values are identified and represented with an amplitudevalue and a location value or time stamp.
 7. A method according to claim1, wherein said identifying step a) includes identification of includedpair combinations of peaks and valleys in said signal.
 8. A methodaccording to claim 1, wherein said identifying step a) includesidentification of included pair combinations of valleys and peaks insaid signal, corresponding to included pair combinations of diastolicminimum pressure (P_(min)) and systolic maximum pressure (P_(max)),characterizing single pressure waves created by the cardiac beat-inducedpressure waves.
 9. A method according to claim 1, wherein saididentifying step a) excludes for further analysis pressure waves duringsaid time sequences with single pressure wave parameters outsideselected criteria for thresholds and ranges of said parameters, saidparameters selected from the group of: starting diastolic minimumpressure defining the start of the single pressure wave (P_(min)),ending diastolic minimum pressure defining the end of the singlepressure wave (P_(min)), systolic maximum pressure of the singlepressure wave (P_(max,)), amplitude (ΔP) of the single pressure wave,latency (ΔT) of the single pressure wave, rise time coefficient (ΔP/ΔT)of the single pressure wave, wave duration of the single pressure wave,and absolute mean pressure of said single pressure wave.
 10. A methodaccording to claim 1, wherein said identifying step a) includes forfurther analysis single pressure waves having single pressure waveparameters within selected criteria for thresholds and ranges of saidsingle pressure wave parameters.
 11. A method according to claim 1,wherein said identifying step a) excludes for further analysis timesequences with time sequence parameters outside selected criteria forthresholds and ranges of said parameters, said parameters selected fromthe group of: number of single waves (N_(SW)), single pressure wavederived heart rate, absolute mean pressure, standard deviation for meanpressure of mean pressure for the individual single waves, standarddeviation for diastolic minimum (P_(min)), standard deviation forsystolic maximum (P_(max)), standard deviation for amplitude (ΔP) of allindividual single pressure waves, standard deviation for latency (ΔT) ofall individual single pressure waves, standard deviation for rise timecoefficient (ΔP/ΔT) of all individual single pressure waves, balancedposition of amplitude (ΔP)/latency (ΔT) combinations, balanced positionof rise time coefficients (ΔP/ΔT).
 12. A method according to claim 1,wherein said identifying step a) includes for further analysis timesequences having time sequence parameters within selected criteria forthresholds and ranges of said time sequence parameters.
 13. A methodaccording to claim 1, wherein said identifying step a) is applied toeach consecutive time sequence in a continuous series of time sequencesof a signal.
 14. A method according to claim 1, wherein said identifyingstep a) further includes selecting single pressure waves which occurbetween two consecutive of said time sequences and placing such waves inone or the other of said two consecutive individual time sequencesaccording to selected criteria.
 15. A method according to claim 14,wherein said selected criteria define that a first of said singlepressure waves within said individual time sequence must have its endingdiastolic minimum pressure value (P_(min)) within said individual timesequence.
 16. A method according to claim 14, wherein said selectedcriteria define that a last of said single pressure waves within saidindividual time sequence must have both its starting (P_(min)) andending (P_(min)) diastolic minimum pressure values within saidindividual time.
 17. A method according to claim 1, wherein saidcomputing step b) for accepted time sequences further includesdetermining said time sequence parameters, said parameters selected fromthe group of: c1) balanced position of amplitude (ΔP)/latency (ΔT)combinations, c2) balanced position of rise time coefficients (ΔP/ΔT),c3) absolute mean pressure for said single pressure waves of said timesequence.
 18. A method according to claim 1, wherein said establishingstep c) includes determining balanced position of amplitude (ΔP)/latency(ΔT) combinations, said determining comprising the steps of creating afirst matrix based on determining number of single pressure waves withpre-selected values related to amplitude (ΔP) and latency (ΔT), one axisof said first matrix being related to an array of pre-selected values ofpressure amplitude (ΔP) and the other axis of said first matrix beingrelated to an array of pre-selected values of latencies (ΔT), andindicating for each matrix cell at respective intersections in saidfirst matrix a number of occurrences of matches between a specificpressure amplitude (ΔP) and a specific latency (ΔT) related tosuccessive measurements of single pressure waves over said individualtime sequences.
 19. A method according to claim 18, wherein the singlepressure wave parameters of amplitude (ΔP) and latency (ΔT) arecategorized into groups, said groups reflecting ranges of said singlewave parameter values.
 20. A method according to claim 18, wherein theoccurrence of matches in said first matrix is indicated through actualnumber of matches during individual of said time sequence windows.
 21. Amethod according to claim 18, comprising the further step of computingbalanced position for a number of occurrences of said single pressurewave parameters of amplitude (ΔP) and latency (ΔT) values duringindividual of said time sequences in said first matrix.
 22. A methodaccording to claim 21, wherein said balanced position of said firstmatrix of numbers of amplitude (ΔP) and latency (ΔT) combinationscorresponds to mean frequency distribution of the different occurrencesof amplitude (ΔP) and latency (ΔT) during said individual timesequences.
 23. A method according to claim 1, wherein said establishingstep c) includes determining balanced position of rise time coefficients(ΔP/ΔT), said determining comprising the steps of creating a secondmatrix based on determining number of single pressure waves withpre-selected values related to rise time coefficient (ΔP/ΔT), the axisin said second matrix being related to an array of pre-selected valuesof rise time coefficient (ΔP/ΔT), and wherein for each matrix cell insaid second matrix indicating a number of occurrences of pre-selectedrise time coefficients (ΔP/ΔT) related to successive measurements ofsingle pressure waves during said individual time sequences.
 24. Amethod according to claim 23, wherein the single pressure wave parameterrise time coefficient (ΔP/ΔT) is categorized into groups, said groupsreflecting ranges of said single wave (ΔP/ΔT) parameter values.
 25. Amethod according to claim 23, comprising the further step of computingbalanced position for a number of occurrences of said single pressurewave parameter rise time coefficient (ΔP/ΔT) in said second matrix, toyield an analysis output.
 26. A method according to claim 25, whereinsaid balanced position of said second matrix of numbers of rise timecoefficient (ΔP/ΔT) combinations corresponds to the mean frequencydistribution of rise time coefficient (ΔP/ΔT) of said time sequence. 27.A method according to claim 1, wherein said establishing step c) yieldsanalysis output related to the absolute mean pressure for said singlepressure waves of said time sequence, corresponding to the sum of meanpressure values for all individual single pressure waves during saidtime sequence divided by number of said individual single pressure wavesduring said individual time sequence.
 28. A method according to claim27, wherein absolute mean pressure for an individual of said singlepressure waves is the sum of sample values during the time of a waveduration, i.e. from starting diastolic minimum pressure (P_(min)) toending diastolic minimum pressure (P_(min)) divided by number ofsamples.
 29. A method according to claim 1, wherein said establishingstep c) yields output of analysis of parameters c1)-c3) during eachindividual of said time sequence windows in a continuous series of saidtime sequence windows of said pressure-related signal.
 30. A methodaccording to claim 1, wherein the duration of each selectable timesequence window lies in a time range of 3-15 seconds.
 31. A methodaccording to claim 1, wherein establishing step c) yields output ofanalysis of one or more of said parameters c1)-c3), said analysis outputbeing presented as numerical values on a display for each of said timesequences during ongoing sampling of said pressure-related signals. 32.A method according to claim 1, wherein establishing step c) yieldsoutput of analysis of one or more of parameters c1)-c3), said analysisoutput being presented as histogram distribution of values of saidparameters c1)-c3) for a selectable number of time sequence windows ofsaid pressure-related signal.
 33. A method according to claim 1, whereinestablishing step c) yields output of analysis of one or more ofparameters c1)-c3), said analysis output being presented as aquantitative matrix for a selectable number of time sequences of saidpressure-related signal.
 34. A method according to claim 33, whereinsaid quantitative matrix is created based on determining numbers of oneof said parameters c1)-c3) with selected parameter values, wherein oneaxis of the quantitative matrix is related to an array of selectedparameter values, wherein the other axis is related to an array ofselected numbers of consecutive included time sequences, and whereinindicating for each matrix cell at respective intersections in saidquantitative matrix a number of occurrence of matches between a specificparameter value and a specific number of time sequences.
 35. A methodaccording to claim 34, wherein said parameter values are categorizedinto groups, said groups reflecting ranges of said parameter values.